Techfastly June 2022

JUNE | 2022

w w w. t e c h f a s t l y. c o m

Edge Computing Edge and Cloud Computing - Can They Coexist Peacefully?

by Toulika Das

p24

How To Implement

Edge Computing in Your Organization?

by Yash Modi

Intel Vision 2022: What Does The Future of Edge Computing Hold?

by Aftab Alam

Redrafting the Hybrid-Remote Workspaces with Voice-enabled Technologies Goutami Garuda

What’s Inside p.4

Edge Computing - The Key To IoT Success byToulika Das

p.14 Edge Computing

Ecosystem: Architecture, Use Cases, and Examples

by Rehan Hussain

p.24

How To Implement Edge Computing in Your Organization?

by Yash Modi

p.34 How End User Computing

(EUC) is Digitally Transforming the PostPandemic Workplace

by Pallabi Das

p.42 Voice-Activated

Technology Must Advance to Support Hybrid Workplaces

p.56

by Goutami Garuda

p.48 Edge Computing and 5G:

The relationship

Data Backups: Critical Part of Cyber Strategy: Strategies to Protect Your Data

by Utsav Mishra

p.64

by Baba Nadeem

Customer service in the digital age. Do we still need human interaction?

Saipriya Iyer

p.78

Edge and Cloud Computing Can They Coexist Peacefully?

Toulika Das

p.92 Intel Vision 2022. What

Does The Future of Edge Computing Hold?

by Aftab Alam

Editor’s note

Dear Readers, Edge computing is a form of computing which takes place on-site or close to a specific data source. This process reduces the necessity for data to be processed in a distant data centre. Edge computing, a modern distributed information technology infrastructure, includes sensors to gather information and edge servers to analyze data in real-time on-site safely. It also works on integrating other devices into the network, such as laptops and smartphones.

Studies show that the COVID-19 pandemic has hastened the development of voice-activated technology.

Considering employees worldwide are expecting greater adaptability and health precautions, voice technology is likely to be a permanent fixture in the workplace of the future. A data backup is a replica or archive of vital information kept on your devices such as a computer, phone, or tablet used to recover that unique data in case of data loss. One can back up their data through external hard drives, cloud backup, or other backup services.

Edge computing will facilitate real-time data analysis via devices on 4G networks, eventually moving to a 5G network.

5G and edge computing are creating new income opportunities in industries like production, transportation, gaming, etc. According to an Accenture poll, 83% of customers prefer engagement with another human over digital technologies. This data suggest that human connection is still necessary in this digital world.

Edge computing seeks to increase the speed of necessary data processing nearer to the device. It suggests that the processing of data is more efficient. There is no requirement for attribute centralization. Edge computing is a mesh interface that allows small data centres to be processed and stored locally. The latest (June) issue of Techfastly magazine discusses the many characteristics and prospects of edge computing technology in depth.

We hope you like reading it, and as usual, your feedback is precious to us.

Looking forward to hearing from you, happy reading!

Srikant Rawat

Chief Operating Officer, Techfastly

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Edge

Computing

The Key To IoT Success

by Toulika Das

T

he manner in which organizations manage data, interpret it, and distribute it via millions of devices across the world is changing, owing to edge computing. The primary reason behind this widespread advancement in the field of edge computing is IoT or the Internet of Things.

Edge-computing systems are being driven by the increasing proliferation of internet-connected gadgets (the IoT), as well as new software that demands real-time computing services.

Experts agree that edge computing will serve a critical role in just about every company's digital transformation. However, development has been sluggish. Organizations have been hesitant to fully utilize the edge for realtime decision-making and resource utilization due to outdated perceptions.

Edge computing systems are accelerating the invention or assistance of real-time applications.

These are video and graphics processing, analytics, self-driving cars, cognitive computing, artificial intelligence, and robotics, to name a few.

IoT - The First Wave of Edge Computing Edge computing has recently gained a lot of attention as a source of potential. Bold concepts like "the edge will devour the cloud" and "real-time automation will extend throughout healthcare, commerce, and manufacturing" are circulating in the business.

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www.techfastly.com

The concept of the edge has been closely identified with the initial wave of the Internet of Things in various sectors. Much of the focus at the time was on gathering data from little sensors mounted to everything and then transmitting that data to a central point, such as the cloud or major data centre.

Processing power closer to the physical device or data source helps to improve the Internet of Things.

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After then, the data flow had to be linked into what is known as sensor-fusion.

Sensor economies, battery life, and pervasiveness at the time frequently resulted in data streams that were too narrow and had inadequate quality. Furthermore, upgrading old equipment with sensors was sometimes prohibitively expensive. While the sensors themselves were affordable, the installation took time and needed the use of qualified individuals.

Finally, the knowledge base of the workforce across enterprises was integrated with the skills required to interpret data utilizing sensor fusion. As a result, IoT adoption has slowed.

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How Can Edge Computing Benefit Internet of Things?

Processing power closer to the physical device or data source helps to improve the Internet of Things. The data which the IoT devices create must be examined at the edge, rather than travelling back to a central site, in order for it to respond faster or reduce issues.

For the data and computational demands of IoT devices, edge computing provides a local source of processing and storage. Here are some of the advantages that we derive from combining IoT with an edge:

1

Reduced Latency

In cases where latency is an issue, edge computing can help. Since it does not travel over a network to the cloud or data centre for processing, it minimizes latency.

The time it takes to process and analyze data is referred to as latency. A connected device's reaction time to the internet is less than a second. The answer may be delayed or halted in numerous scenarios. www.techfastly.com

It occurs when there is a problem with the internet connection or when the data centre is located far away from the device. In such instances, the data processing speed is slowed. In order to compensate for the delay of data transmission across long distances, computational resources should be local.

2

Bandwidth

Cloud computing is used by businesses to handle and analyze large volumes of data.

For the purpose of transferring data to the cloud, large quantities of electricity and bandwidth are required in the case of IoT. To gather and analyze data, IoT devices that create data and run software need to be linked to the cloud. Businesses may use edge computing to reduce their internet bandwidth use. Large volumes of data may be managed in close proximity to the source.

Another issue that companies had to deal with was the cost of operation. IoT devices create massive amounts of data and deliver minor updates to the cloud that aren't essential. Because this procedure needs more

bandwidth, the cost of bandwidth rises. The cost of the gadget to get to that bandwidth and the price of storage and analysis rises.

This data may be collected and analyzed locally before being sent to the cloud via edge computing. It will be far less expensive than transmitting unfiltered data across expensive WAN networks.

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Underlying Security Issues in IoT

Organizations are committed to protecting the privacy of their essential data, regardless of the fact that the cloud provides great protection for their IoT applications. They fear that the data will be insecure once it reaches the cloud and departs their company's premises. Edge computing can overcome this very obstacle by introducing additional security at the edge. This will increase the security of data storage and operations against hackers and assaults. Security can be adjusted on edge devices, for example, any outage will be limited to that particular device and its applications.

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Taking IoT 1.0 to the Next Level The edge is present in every aspect of our lives: where we reside, operate, and where human activities take place. Improved and far more flexible sensors have overcome the problem of sparse sensor coverage.

New assets and technologies come with a variety of built-in sensors. Sensors are now frequently supplemented with highresolution/high-fidelity images (x-ray equipment, lidar).

Further sensor data, image technologies, and the need to correlate all of this results in terabytes and megabytes of data being generated each second. Compute firepower is increasingly being installed near where the data is created to drive outcomes from these massive data flows.

The explanation is quite simple: between the edge site and the cloud, there is just insufficient bandwidth and time. In the short term, the data at the edge is most important.

Data may now be evaluated and used in realtime at the edge rather than being processed and analyzed later in the cloud. Computing at the edge is required to achieve the next level of efficiency and operational excellence.

Proper understanding of massive data streams across a large number of geographically scattered sites is what the edge is all about. To properly comprehend what is now possible with edge computing, one must embrace this new perspective of the edge.

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The Present Scenario of Edge Computing Instead of a few sensors at the edge, data may now be generated from a large number of sensors and cameras. Following this, the data is then evaluated at the edge using computers that are thousands of times more powerful than those used only two decades ago — all at affordable prices.

Real-time edge analytics is now a reality because of the availability of high-core-count CPUs and GPUs, as well as high-throughput networking and high-resolution cameras. Companies may better understand their processes and respond faster by deploying real-time analytics at the edge (where business action occurs). Some basic benefits of edge computing for IoT are:

Increased operational efficiency and faster reaction times.

Network bandwidth has been increased.

Analytics algorithms and machine learning provide local data processing, aggregation, and quick decision-making.

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When a network connection is lost, the system continues to operate offline

An IoT gateway can send data back to the cloud or a centralized data centre from the edge, or it can deliver data to edge equipment to be processed locally. www.techfastly.com

By 2023, more than half of the new company IT infrastructure deployed will be at the edge rather than business data centres, rising from less than 10% now. By 2024, the number of applications installed at the edge will have increased 800%.

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Anti-fraud Measures in Supermarkets Self-checkout is now widely used in supermarkets, and sadly, it has resulted in an upsurge in fraud. A shady shopper might exchange a lower-priced bar code for higherpriced goods, resulting in a lesser charge.

Stores are increasingly deploying highpowered cameras to identify this form of fraud by comparing scanned products and weights to what they should be. Despite the fact that these cameras are very affordable, they create a large amount of data. Data may be evaluated in real-time by bringing computers to the edge. This implies that instead of waiting until the "buyer" has exited the parking lot, shops may identify fraud in real-time.

Food Production Monitoring System Using IoT

At each stage of the manufacturing process, a manufacturing plant may now be outfitted with a slew of cameras and sensors. Real-time analysis and AI-driven inference can indicate if something is incorrect or if the process is straying in milliseconds, if not microseconds.

Perhaps a camera indicates that too much sugar is being added or that an item is being covered with too many garnishes. Production lines may be modified to halt the drift or even stopped if repairs are needed, utilizing cameras and real-time analysis — all without generating disastrous wastage.

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Edge AI in the Healthcare Industry The current healthcare business is being shaped by edge computing. As previously stated, there are several advantages to using Edge AI. It may be extremely important for both patients and healthcare practitioners in the healthcare business. It provides autonomous monitoring of hospital rooms and patients using computer vision and data from other sensors.

Consider the case of an accident due to fall detection. Several wearables now have the capacity to detect whether a person falls unexpectedly by utilizing particular technology. These gadgets' edge AI can be trained to detect falls in real-time and even notify caretakers. In most circumstances, this can save a person's life. www.techfastly.com

Role of Edge Computing in Autonomous Vehicles Autonomous cars are now conceivable because of affordable and widely accessible cameras that provide 360-degree stereoscopic vision.

Analytics also enables accurate picture identification, allowing the computer to distinguish between a tumbleweed and the neighbour's cat – and determine whether it's safe to stop or steer past the obstruction.

The real-time pattern recognition and vector planning that is the driving intellect of autonomous cars is enabled by the cost, availability, and compactness of the high-powered GPUs and CPUs.

The Future of Edge Computing in IoT IoT, or the Internet of Things, is driving the demand for Edge Computing due to very useful applications. Edge computing helps to bring the cloud closer to the edge of the network.

Edge Computing is not a replacement for the cloud; rather, the two work together in a symbiotic way. Despite the fact that several companies are creating tools to manage this new infrastructure, there is still no standardization. Edge Computing will undoubtedly continue to expand and become increasingly common. As these technologies are embraced by many sectors in the IoT ecosystem, there is still a lot to discover about them.

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Edge Computing Ecosystem Architecture, Use Cases, and Examples

by Rehan Hussain Edge computing brings AI and analytics workloads closer to where data is created, and actions are taken—reducing latency, decreasing network demands, increasing the privacy of personal and sensitive information, and improving operational resilience.

- Rob High, IBM Fellow, VP & CTO, Networking & Edge Computing, IBM Cloud

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The edge architecture is a distributed computing architecture that incorporates every component active in edge computing—everything from devices to sensors to servers to clouds—wherever data is handled or utilized in remote areas of the network.

The term "edge computing" refers to processing data at the place closest to the source or destination of the data in a system— where it comes from or goes to.

Using the term "edge computing" connotes a physical location. Instead of depending on the "bigger" clouds to perform all the work, it is computing that is done at or near the source of the data. An advantage of edge computing is that it brings corporate applications closer to the areas where data is generated and action is required.

What is the source of all this information?

Devices that govern data flow at the network boundary are edge devices. With the rise of cloud computing and the Internet of Things (IoT), the importance of edge devices has increased, necessitating more intelligence, computation, and AI services at the network's edge.

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Edge computing architecture is an ecosystem of infrastructure components that have been spread out from the central location of an enterprise's data center or main server to all of the company's other locations.

By lowering latency and lag, edge design speeds up processing. As a result, applications and programs running at the edge can perform better for the user and enhance overall performance. Each dock where goods are loaded and unloaded and inspecting the product before it leaves the pier is an example of an "edge" for a shipping firm. Even if your company's primary data center is remote, the edge is where your apps are being processed.

What is Edge Computing?

With edge computing, you not only get a lot of data from a lot of different devices, but you also have to make sense of all that data and let the devices decide for you. We will talk about IBM's offer and how to design an edge solution, and the different parts that make it up.

Use cases from different industries that deal with scalability, latency, and security will be shown.

Edge computing architecture is an ecosystem of infrastructure components that have been spread out from the central location of an enterprise's data center or main server to all of the company's other locations. This is part of the company's overall deployment. Computing and storage capabilities, applications and devices, and sensors are all part of this. They work together with IoT devices in a central data center or cloud.

When we talk about edge computing, they have enough bandwidth, memory, and processing power to collect, process, and act on data in real-time without the help of other parts of the network, so they do not need to ask for help from other parts of the network. Some connection with the network lets the device talk to a database in a single place. It is easy to move scaled-down, onpremises edge servers or data centers around and fit them into small remote places. Red Hat has a wide range of flexible topology options that can be used in small spaces or different environments, such as power/cooling and intermittent network connectivity. This is just one example of what Red Hat can do with edge computing.

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Key Components of Edge Ecosystem

A Cloud

Clouds can be public or private, and they can be a place to keep the container-based workloads like applications and machine learning models that run on them. Also, these clouds run and host the applications that are used to manage and orchestrate all of the different edge nodes. There will be many interactions between the workloads on edge and the workloads on these clouds. The cloud can also be a source and a destination for any data that other nodes need to do their jobs well.

Loads are apps that need to run on this architecture layer because they cannot run 18

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on the other edge nodes or the management layers. Both application and network workloads need to be moved to different edge nodes by using suitable orchestration layers.

B Edge Hardware

An edge device is a piece of equipment made for a specific purpose and has a lot of computing power. Many exciting things can be done with edge devices. These include an assembly machine on the factory floor, a cash machine, an intelligent camera, or a car that can see things. People often see edge devices with ARM or x86 class CPUs with 1 or 2 cores, 128 MB of memory, and maybe 1 GB of storage that is not on the device itself. Edge devices www.techfastly.com

can be more powerful, but they are not the norm now.

They are the systems that are on-site or at the edge of the network. They can be separate physical or virtual servers in different places, or they can be combined in a system called a hyper-converged system. There are two main parts to this layer of the architecture. It will be home to both the parts of the systems that will run these applications in these architecture layers and the applications on the edge of these devices.

Application Layer: People who want to run big apps that cannot run at the edge because they are too big for the device will run these apps in this layer. Video analytics and IoT processing are two examples of complex applications.

Network Layer: Physical network devices aren't usually used because it's hard to keep them up and running. Almost all of the network layer has been virtualized or containerized.

These could be routers, switches, or any other network parts needed to run the local edge.

C The Edge Node

An edge node is a general term for any edge device, edge server, or edge gateway that can be used for edge computing. It can be used to refer to any of these things, such as cameras, sensors, and other physical devices that run on-site at the edge are called edge devices. A simple edge device can either collect or send data, or both, simultaneously.

The more complex edge devices have more processing power to do more things. In either case, it is essential to be able to put and

manage apps on these edge devices so that they can work. Specialized video analytics, AI models that learn quickly, and simple realtime processing apps are some examples of applications that use this type of technology.

IBM uses its IBM edge computing solutions to run and manage containerized applications on these edge devices.

D Edge Cluster or Server

An edge cluster/server is a generalpurpose computer that is used in a place where people work, like a factory, retail store, hotel, distribution center, or bank. An edge cluster/server is usually made from an industrial PC or a computer rack. People often find edge servers with 8, 16, or more cores of computing power, 16GB of memory, and much storage, like hundreds of GBs. An edge cluster or server is usually used to run enterprise application workloads and other shared services, such as email.

E

Edge Gateway

"Edge gateways" are usually edge clusters or servers that, in addition to running enterprise applications and sharing resources, also have services that can do things like translate protocols or connect to networks. A few edge devices can act as a limited gateway or host network function, but most edge gateways are separate from edge devices.

Fixed-function IoT sensors collect and send data to an edge/cloud, but they do not have onboard computer memory or storage.

Let's discuss a few use cases to understand the power of edge computing and how it will rule the world in the future.

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Real-life Case Studies: There is a plethora of problems to be solved in every complicated workplace. On an individual basis, it will be necessary to decide if an edge computing solution is warranted for a given business challenge or use case. The following are some possible industrial use cases, as well as real-life solutions, for reference.

CASE STUDY #1

SMART CITIES

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Due to aging infrastructure, operational inefficiencies, and increased demands from inhabitants, operating and regulating cities has become an arduous undertaking. New technologies, such as IoT, edge computing, and mobile connection have made it easier for innovative city solutions to gain traction with residents and municipal officials.

www.techfastly.com

IoT is the foundation of every smart city solution. These devices may be embedded within the city's infrastructure and assets to monitor the functioning of these assets and offer meaningful information about their behaviour. Edge computing is a prerequisite for delivering the city's mission essential solutions, such as traffic, flood, security and safety, and critical infrastructure monitoring, due to the need to give a real-time decision and avoid transferring a significant quantity of sensor data.

These devices may be embedded within the city's infrastructure and assets to monitor the functioning of these assets and offer meaningful information about their behaviour.

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CASE STUDY #2

MANUFACTURING SECTOR As a result, a quick reaction is vital for reducing product failures and increasing efficiency in production. To maximize the efficiency of each machine, analytical algorithms keep track of how well it's performing and adjust the settings—predicting when a failure will occur and scheduling maintenance between runs may be done with the use of analytic algorithms. Using different edge devices, it is possible to send important information to many edges, including the cloud.

Take a look at this: Reducing downtime is a priority for an electric bicycle manufacturer.

Factory floor equipment includes presses, assembly machines, robots for painting, and

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conveyors. You lose $250,000 per hour if there is a problem with a manufacturing run.

Making a profit is the difference between a company operating at maximum efficiency and experiencing unanticipated interruptions.

The following are required to keep the factory running at maximum efficiency for it to function smoothly:

A

Methods for analyzing equipment performance and adjusting its operational settings to maximize efficiency.

B

To plan maintenance on equipment in between runs, you'll need algorithms that can identify and forecast failures.

C

To accurately predict failure, models specific to each use case must be developed.

www.techfastly.com

Conclusion Edge computing is constantly changing and getting better. It uses new technologies and practices to improve its abilities and performance. Edge availability is one of the most important trends, and edge services are expected to be available worldwide by 2028. There are many different ways that edge computing can be used right now, but the technology is expected to become more common and change how the internet is used in the future. This will bring more abstraction and use cases for edge technology. In fact, there have been a lot of new products for edge computing, like computers, storage, and network appliances that are made for this type of technology. More multivendor partnerships will make it easier for products to work together and be flexible at the edge. There is an example of this, which is when AWS and Verizon work together so that the edge can get better connectivity.

Wireless communication technologies, such as 5G and Wi-Fi 6, will also impact edge deployments and use in the coming years.

These technologies will allow for virtualization and automation that has not been explored yet, such as better vehicle autonomy and workload migrations to the edge, while making wireless networks more flexible and cost-effective.

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How To Implement

Edge Computing in Your Organization?

by Yash Modi

Autonomous robots, self-driving cars, and retail robots are all instances of edge computing in action. You will become a big fan of edge computing in the fast-food industry. The restaurants can use data from cuttingedge equipment to determine the ideal cooking time for the fries. It's possible to customize these actions thanks to edge computing technologies. A day's worth of transactional sales data may be used to swiftly generate a cloud forecast of how many waffle fries should be cooked each minute. In addition, you'll be quick to keep up with the latest developments!

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Services may be supplied quickly and efficiently yet with a personal touch. This is feasible via the use of edge computing.

www.techfastly.com

What Does "Edge Computing" Mean?

Edge computing is based on IoT sensors; it is a distributed IT infrastructure that analyzes raw data close to its source. This technique spreads the load across several computers rather than relying on a single computer to manage an infinite stream of traffic from various devices. As a result, only actionable discoveries are sent to the central server, often in a more energy- and rent-efficient location.

Compared to frameworks based on remote centralized servers, they are offloading certain operations to the periphery, resulting in increased bandwidth and latency.

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Edge Computing Use Cases Due to the fast rise of the Internet of Things (IoT), edge computing capabilities and use cases have expanded substantially. Consequently, edge computing has a plethora of applications, of which these are only a few.

Equipment uptime and maintenance costs may be reduced by using adaptive diagnostics in manufacturing.

Combining edge-computegenerated error codes and previous repair information may help professionals quickly identify and fix problems.

Using edge computing, it is now feasible to monitor the efficiency of public buildings and facilities, such as lighting and heating. In addition, traffic cameras and signals may help improve traffic flow and safety.

When near-zero latency is required, real-time edge computing will become most apparent and dramatic shortly in autonomous vehicles.

Reminders for medications might be transmitted to a wearable device that monitors your heart rate, body temperature, and other vital indications.

Consequently, developers may use edge computing to ensure that sensitive data is never sent outside the device, such as medical photos.

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www.techfastly.com

Why Is It Necessary to Implement Edge Computing?

It would be best if you first created a compelling business and technical edge strategy to adopt the technology properly.

It is not a matter of selecting vendors or equipment in this instance. Rather than that, an edge approach recognizes the value of edge computing. It comprehends the "why" demands a thorough understanding of the organization's technological and economic issues, such as circumventing network constraints and preserving data sovereignty.

Preparation and migration techniques are critical for an edge data center Such initiatives may begin with discussing what the edge means, where it exists for the company, and how it should benefit the organization. Businesses and technology roadmaps need to be aligned with the strategy's goals to be effective.

For example, edge and other distributed computing technologies may align well with the company's need to shrink its centralized data center footprint.

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Choosing the proper hardware and software is critical as the project nears completion As far as scale and scope go, edge computing initiatives can include a few pieces of locally installed computing equipment in a ruggedized enclosure atop an infrastructure facility to thousands of sensors feeding into one single high-speed, low-latency network connection to the public cloud. There are no two deployments of the edge that are the same. Edge strategy and planning are crucial to the success of edge projects because of these variances.

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Comprehensive monitoring is required when using an edge deployment If IT workers don't make it to the edge location, edge installations should offer resilience, fault tolerance, and selfhealing capabilities. In addition, tools that monitor remote deployments must be simple, provide full alerting and reporting capabilities and keep the installation and its data safe from unauthorized access and intrusions. Site availability, network performance, storage capacity, usage, and computing resource utilization are just a few examples of the metrics and KPIs often used in edge monitoring. www.techfastly.com

And no edge implementation would be complete without careful consideration of edge upkeep

SECURITY

CONNECTIVITY

Consideration should be given to tools that focus on vulnerability management and intrusion detection. Security measures must include sensors and IoT devices since each network piece might be breached, opening the door to many potential attack points.

Another difficulty is a connection, and it is necessary to provide mechanisms for access to management and reporting even when connectivity for the actual data is unavailable.

Specific edge installations provide backup connectivity and control via a secondary connection.

MANAGEMENT

MAINTENANCE

Because of the remoteness of edge installations, remote administration and provisioning are required. Managers of IT systems must be able to monitor and control deployments at the edge.

It's important to remember that physical upkeep is essential. Standard battery and device replacements significantly reduce the useful life of Internet of Things (IoT) devices.

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How To Deploy Edge Computing?

There are several edge computing solutions and price models. However, when seen from the client's perspective, three distinct models emerge. After examining many different methods to edge computing, it's time to consider why a corporation might choose one over another.

A

Public Cloud-managed Edge Computing (CSP)

Most big organizations use the public cloud for a variety of functions. Consequently, extending a cloud partner's services and administrative processes to urban edge locations may seem appealing. CSPs such as Microsoft Azure, Amazon Web Services, and Google Cloud extend their reach by establishing regional expansions of their cloud platforms to offer processing power closer to end customers. However, for customers who now host their apps and data with one of these cloud providers, the most straightforward approach to the edge will be through their existing cloud service provider.

B

LTE and 5G Telecom Providers Control Edge Computing Owing to the sensitivity of their business, telecommunications providers have an advantage over CSPs when it comes to local edge deployment. Since carriers often have national networks, customers may lease small-footprint data centers from carriers for edge computing purposes. For edge computing, telecommunications firms will heavily rely on LTE and 5G mobile networks.

The fastest way to achieve the lowest possible latency for mobile consumers and devices is to integrate edge services directly into the LTE/5G carrier's infrastructure.

This technology, dubbed multi-access edge computing (MEC), is already available from major US telecommunications carriers such as AT&T, T-Mobile, and Verizon.

C

On-premises Hosting of Edge Computing Systems

The ability to put cloud hardware in private data centers or colocation facilities is another option that cloud providers give to their corporate clients. Use cases where most users and devices that demand high bandwidth and low latency services are situated inside the corporate network are suited for these solutions.

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Challenges and How To Address Them In The Future?

Edge computing is projected to see widespread adoption as it complements cloud computing and gets closer to a more distributed network.

Gartner estimated that the IoT would reach 50 million devices in 2020. Additionally, IDC research indicates that data is growing at a two-year rate, and by 2025, there will be around 80 billion devices connected to the internet, about double the present data. As a result, firms will encounter new challenges in offering seamless and secure services to their users due to the extraordinary development in digital business efforts and increased data collection.

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www.techfastly.com

Consequently, edge computing will gain relevance in this environment, assisting enterprises in eliminating bottlenecks.

The Bottom Line Considering edge computing is decentralized, success needs meticulous architectural and implementation planning.

Additionally, it's challenging to create a one-size-fits-all strategy in today's fast-paced data collection and analysis world.

However, by cooperating with a respected partner at any point of the journey, you may gain a competitive advantage.

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Any internet-connected device must respond in milliseconds or less. Latency is a word used to describe a delay in communication between a network and a device. Edge computing eliminates latency issues since it operates on the premise of a more dispersed network, ensures that real-time information processing is not interrupted, and provides a more stable network.

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Second, the outage would only affect the edge computing device and its local apps. New or existing systems may be integrated with APC by Schneider Electric to detect and prevent power issues before they arise.

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Edge computing sites deliver real-time data and alarms without interruption. An effective monitoring system may prevent and correct problems even before they develop.

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As a result, edge computing reduces capital expenditure and operational costs. To keep costs down, APC by Schneider Electric's solutions may be integrated with new or existing hardware and software and can be configured to expand as your needs change. The remaining IT infrastructure will be rewarded with a 75% * payback.

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Creating a data culture that meets industry standards and complies with data rules is a top priority for any firm. Schneider Electric's APC provides end-to-end services that satisfy all needs.

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Post-pandemic Workplace Transformation

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How End User Computing (EUC) is Digitally Transforming the Post-Pandemic Workplace

by Pallabi Das

The COVID-19 pandemic not only impacted our lifestyles but also affected the way we work. In the aftermath of this pandemic, work from home has become immutable and irreversible. No one anticipated that working from home would be the new 'normal.'

Microsoft recently stated that the hybrid working models would be the future, based on findings and considerations of work trends over the past few years. Organizations accepted the emerging expedition of digital transformation, and some were even forced to pursue it because of the pandemic. As a result, those companies that weren't planning to move to the cloud became compelled to do so within a matter of days or weeks.

Post pandemic transformation is also accelerating among a majority of organizations. As business leaders reflect on current conditions or look forward to the future, their demands for speed and flexibility have dramatically increased. An unprecedented pace of change is pushing aside old barriers under the pressure of unrelenting disruption, rapidly evolving customer expectations, and implacable disruption.

This article will give you an idea about what end-user computing is doing to transform the post-pandemic workplace digitally.

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Post-pandemic Workplace Transformation The COVID-19 pandemic has disrupted businesses globally in 2020. One of the most obvious outcomes of COVID-19 is that more employees are working remotely.

Several companies monitor employee satisfaction and well-being to better understand employee experience, while others monitor productivity.

Organizations have implemented ways to collaborate digitally and attain maximum productivity through means such as enduser computing. With remote working going on, the means to monitor employee performance are also transformed digitally.

Organizations have begun using virtual login and logout tools, tracking work on computer usage, and monitoring employee emails or internal communications/chat. Moreover, team meetings or calls are now conducted via virtual means such as Microsoft Teams, Google Meet, Zoom, etc.

It is also seen that the pandemic has increased the trend of employers playing an expanded role in their employees' financial, physical, and mental well-being.

A variety of benefits are also available to employees, including enhanced sick leave, financial assistance, and flexible hours.

What is EUC? In technical terms, End-User Computing (EUC) refers to the computing platforms or environments that help non-programmers create working applications. The EUC technology allows end-users to manage and control their applications without the assistance of programmers or developers.

The core developers or programmers build a highly flexible computing environment that you can easily manage yourself as an end-user. EUC is highly beneficial for those offices that have mobile workforces or work from home employees. It leverages virtualized infrastructure to address the needs of employees and the organization. In its most

basic form, end users work with a series of centralized applications and services to maintain a cohesive workflow. End-user control connects users with department standardized applications and hardware depending on the user's role.

End-user development means the users leverage a set of tools that allow them to create and customize new applications.

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Two Ways You Can Implement EUC EUC can be implemented into business in the following ways:

A

Cloud Services

End-user computing has made it possible for everyone to work from anywhere. It has become possible to work from a movie theatre or even an amusement park in today's world. This is possible because of devices that support such strong connectivity. In simpler terms, businesses are gaining a lot more profit by adopting cloud services.

It has decreased the dependence on client apps that have to work across multiple operating systems. End-user computing implemented through the cloud has made it easier for both employers and employees to access the work apps and tools required to get the job done via a browser or an efficient, lightweight mobile platform.

Cloud services showcase four advantages, namely

Increased productivity

Secured infrastructure

Improved collaboration

Strengthen engagement

B

Virtual Desktop Infrastructure

Companies and organizations with large data centers are able to provide their employees with access to their desktops from anywhere, using a Virtual Desktop Infrastructure (VDI) setup. Virtual desktop infrastructure is a technology for running and managing the desktop operating system in a data center, typically using Microsoft Windows. It falls under the category of end-user computing (EUC) to present virtualized applications and desktops to users. Upon accessing the virtual desktop, it becomes the user's primary focus, and it appears and feels just like local workstation users can select the appropriate applications and perform their tasks. Whether that user is accessing VDI from a workstation, a home computer, or a mobile device, the user interface stays the same, with no need to acclimate to any physical platform. Also, an on-premises VDI provides significant security benefits.

Upon accessing the virtual desktop, it becomes the user's primary focus, and it appears and feels just like local workstation users can select the appropriate applications and perform their tasks.

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How Has EUC Transformed The Business?

Users today operate in a heterogeneous environment, so acknowledging end-user computing is essential. Modern users may be working with virtual apps, internal apps, native mobile apps, or SaaS (Software as a Service) web apps, either through their Windows computer, Mac system, or iOS tablet. They might be working at home, at the office, or even connected to public Wi-Fi. The variety of apps, devices, and work styles has led to changes in EUC over the years. The major shifts in EUC occurred only over the last decade when the constituents of this new model were required to adapt to the fast-changing business needs. Web and SaaS apps have become more feasible alternatives to Windows applications, and mobile devices have made a rapid transition from just being portable email machines to

devices that can replace computers for many tasks. Above all, mobile devices are becoming powerful enough to facilitate and support new business models.

The IT industry shifted away from its old, traditional role as entirely in charge and has become more consumerized.

For this reason, there is a paradigm shift in EUC services, such that they can address the growing consumerization and change digital preferences.

Advantages of EUC The following are the main advantages that EUC can bring to your business:

1

Centralized IT Management

A traditional IT environment at the enterprise level comprises hundreds or even thousands of physical computers.

EUC solves this issue with centralized management. You can manage multiple desktops and devices from a unified interface. You can install updates, patches, applications, software installation, operating systems, and more through a 40

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centralized workstation. This provides your enterprise with unrivaled agility and reduces administrative overheads.

2

Flexible Computing Service

Combining EUC and the cloud in the form of virtual desktops gives you unprecedented flexibility while working. You can work from any location and operate from personal devices like phones or laptops. www.techfastly.com

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Enhanced Automation

Most of the steps involved in computing the delivery of resources are automated using EUC services. By utilizing these services, you can improve efficiency and reduce the employee's workload so that they can spend more time on other tasks.

4

Improved Testing

One of the key benefits of using this type of system as opposed to the traditional IT model is the ability to build prototypes and publish them for testing quickly. Businesses can use the opportunity to save time and money by constructing a user-friendly application. This focuses on improving the actual user experience.

5

Highly Secure End-user Environment Combining EUC with cloud infrastructure is the answer to having a secure endpoint device.

Data is stored in high-security safeguards like DDoS protection, OS patching, multi-factor authentication, and firewalls.

Conclusion The end-user has already proven critical in aiding businesses in sailing smoothly through the COVID-19 scenario. Companies may consider making the work from home model permanent despite favorable market conditions. Looking at all these prospects, organizations will stick to and adopt every service that will help them get the work done on every device and every network. Businesses are focusing more on a user-centric approach that will maximize the availability of the applications and increase workforce productivity. Thus, the future of any productive work will be based on end-user computing.

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Voice-Activated Technology Must Advance to Support Hybrid Workplaces

by Goutami Garuda Post-2020, there have been massive shifts in how we work, learn, and interact with the world. Remote working, streaming services, and online deliveries did exist even before that, but now they have become mainstream and "better alternatives." People who spent over 10 hours a day in offices/schools or outside their homes now prefer to stay at home and depend on technology to conduct daily activities, including performing jobs or running businesses. Virtual assistances or voice commands integrated into devices have made these technologies more convenient to use. Voice assistance, touch-less payments, and self-checkout kiosks are the new staple, but how inclusive are these technologies and what lies ahead for voice and speech-activated technologies?

Let's take a look at the future of hybrid workplaces, how the voice-and-speech activated technologies have evolved over the years, and how diversity and inclusion in hybrid workspaces can be elevated with technology.

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Companies Are Now Supporting Hybrid Workplace Discussions around hybrid working models are increasing as companies and employees contemplate the success of the remote or hybrid models. The pandemic may or may not be over, but remote working is here to stay in some form or the other. There is no doubt that technology-based companies are the first to adopt the remote working models as they are already used to Zoom, Slack, SharePoint and other similar applications. But does this work for more "traditional" companies and sectors too?

Companies that support the hybrid working models are again of different types – the office-centric, the flexible hybrid, the remotefriendly hybrid and the virtual-first, depending on the systems in place and also the senior management's approach towards remote working. The hybrid-remote option is the most popular because it gives employees greater flexibility to work at their own convenience and avoid certain challenges that come with office working – lengthy commutes, inflexible working hours, daycare for children, and so on.

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The transition to hybrid remote working is interesting – it started suddenly with mandatory all-remote and ended with some companies practically giving up all of their working spaces altogether and embracing complete remote working (3M, Aquent, Atlassian, Coinbase, among others). The current trend supports a hybrid model by both employees and employers because no one is sure of the future anymore. The hybrid model gives companies the flexibility to go back to either all-remote or all-office, depending on the requirement. Some companies that have adopted the hybrid working model are HubSpot, Dropbox, Reddit, Shopify, Twitter, Slack, Grammarly, Mailchimp, Adobe, LinkedIn, Uber, Cisco, Intel, Microsoft, Unilever, Zoom, Deloitte and many more.

How Has Voice Technology Evolved Over the Years?

Post the COVID-19 pandemic, the demand for voice and speech recognition technology has steadily increased and is expected to reach over $20.9 Billion by 2026, up from $7.7 Billion in 2020. The increasing use of smart devices and extensive adaptation of mobile technology are responsible for an almost 18% CAGR for this market. Rapid advancements in this technology, enabling devices to recognize speech patterns, accent, pitch, and even speaking styles using Machine Learning, NLP (Natural Language Processing), and Artificial Intelligence have contributed to more and more of its adoption in all kinds of devices. Furthermore, its applications in IoT (Internet of Things) devices, smart wearables, automobiles and in-car systems and biometric devices are likely to boom as the technology advances.

The development of speech and voice recognition technology dates back to the 1950s when Bell Laboratories developed "Audrey," a system that could recognize 1-9 numbers when spoken aloud. The next major advancement was the creation of 44

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IBM engineer William C. Dersch, shown above in 1961, demonstrates Shoebox, an experimental machine that performed arithmetic on voice command.

Image source: www.ibm.com

IBM's "Shoebox" in the early 1970s, which used the sound and pitch of phonemes to construct a word and then match it against preprogrammed information to determine what word was being said. In the 1970s, the Department of Defense invested in the DARPA's Speech Understanding Research program resulting in the development of

"Harpy," a system that could understand over 1000 words.

The 1970s and 1980s saw much more advancement in speech and voice recognition technologies and made their way into children's toys - Speak & Spell and Julie doll, the latter being advanced enough to distinguish between different speakers. The major leap in voice recognition technology came when developers started using NLP with algorithms to program systems that become educated in syntactic, semantic, and tonal rules. The Hidden Markov Model, for instance, uses statistics and probability to understand a specific sound like a word. These were big steps above using just sound to recognize the words. In 1990, Dragon brought out the "Dragon Dictate" speech recognition system and the "Naturally Speaking" system in 1997.

Despite these advancements, there was no practical application of this technology on a large scale, even by big enterprises, because of their limited processing power and memory and challenges in recognizing global accents.

Google's Voice Search App, released in 2010, paved the way for modern cloud-based speech recognition technology. Its success led to the development of Siri in 2011, which was hugely successful across the world for its ability to interpret speech patterns and process natural utterances accurately. Siri was followed by Amazon's Alexa and other devices that used modern speech recognition technologies and became a part of several devices. The best part is that they support a wide range of languages and accents with amazing accuracy.

Voice-Activated Technology for Supporting Diversity and Inclusion in Workspaces So, what do these advancements in voice and speech recognition mean to the modern man?

Will they make lives easier? Will they make learning smarter? And will they recognize the diversity of the global workforce? The answer is "Yes" to all of these, says Michelle Arentz, owner of Lazarus Learning LLC. Speaking about the pandemic and how it has affected many workers and students who had to go "online" suddenly, Ms. Arentz feels that textto-speech technologies can play a very crucial role in online learning support, communication among and with frontline workers, and the work-from-home situations.

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by as many people as possible, says Cathy Pearl, head of conversation design outreach at Google. Ms. Pearl says that although AIpowered VUI devices provide convenience to the average user by enabling a more frictionless and natural experience, the future of VUIs includes a much bigger stage: empowering the people who need it the most. They have the ability to make people with motor or mobility and visual impairments become more independent and also more inclusive in the workplace. This becomes all the more relevant in the remote hybrid working models based on effective communication, collaboration, and productivity that these voice-activated technology devices can promote. www.techfastly.com

Voice-Activated Technologies in Hybrid Workspaces Voice-activated technologies can be a boon for hybrid workspaces as they can help to connect the employee with the work environment from anywhere seamlessly.

For instance, Tact.ai is a hands-free, voiceactivated software that can automatically dig up information from emails, research reports, and archives. Similarly, ServiceNow in Singapore has installed voice-activated booking systems where meeting rooms can be set up remotely, complete with a video system. Automated security clearances, maintenance checks, ordering office supplies,

1 4

Recognize a number of dialects and accents, including speech impediments, Offer more safety and security features integrated within the technology,

2 5

adjusting ambient light and temperature based on occupancy, troubleshooting systems, onboarding new employees, rolling out updates, and technical support can all be managed remotely through voice controls.

Skill-driven workspaces like hospitals and factories can pull up critical data through voice commands without any manual intervention.

Future advancements in voice-enabled technologies should be based on developing algorithms that

Have speakers that can navigate ambient noise and background voices Provide acoustically optimized workstations or special spaces

3 6

Integrate the technology with laptops and computers used in the workplaces Create tech-enabled meeting rooms that voice commands can control- the possibilities are endless.

Conclusion Voice and speech-activated technologies have no doubt come a long way with advancements and are set to revolutionize modern workspaces. Hybrid working models are here to stay because they provide the balance between how things were and how they are now. The idea behind voiceenabled technologies is to make this hybrid working successful and also improve employees' productivity by letting them do a myriad of activities with simple, hands-free commands. Alexa for Business and Zoom for Home and Cortana are examples of integrating virtual assistants with smart devices and office/home workspaces.

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Edge Computing and 5G How are They Connected

by Baba Nadeem Taking compute and data to the edge is steadily gaining momentum.

But with today's data explosion and evolution of end devices, network infrastructures that can handle large data volumes and increasingly complex edge devices are in high demand. The combination of 5G and edge computing appears to be the answer to this problem.

One millisecond is the minimal latency offered by 5G, with the restriction that one millisecond is only radio latency.

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Edge Computing and 5G A symbiotic link between 5G and edge computing technologies can support a new generation of smart devices and apps. 5G's improved capabilities can boost computer applications by lowering latency, enhancing application response times, and expanding data collection and processing capabilities.

With the increased number and capabilities of edge devices, the Internet of Things (IoT) devices are becoming increasingly complex.

Because they can collect numerous types of data, IoT devices are becoming increasingly complicated. The data created by these 50

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devices raises the demand for underlying data to help organizations stay on top of trends, predict new products and services, and gain a competitive advantage.

Every day, humans generate more than 2.5 exabytes of data. Consider sending a 1.7 megabytes per second route to be processed for everyone on the planet. www.techfastly.com

This can put the network under a lot of strain, resulting in performance issues, including latency, back-to-back delays, and bandwidth abuse. The necessity for 5G and the computer edge to function together is reinforced by large volumes of data, the difficulty of transporting data, and the inefficiencies of remote computing.

Furthermore, because the COVID-19 outbreak has caused traditional employment patterns to change, there are additional responsibilities for surrounding equipment. With the increasing quality of computer cases and data requirements, this design necessitates a short control loop to meet near real-time reaction requirements. As a result, 5G network infrastructure can support and enhance cold complexity and expertise in edge computing.

Benefits of the Relationship Between 5G and Edge Computing

1

Low Latency

To achieve ultra-low latency across a wide range of devices and operational situations, the combination of 5G and edge computing is necessary. 5G pairing and edge computing address the growing demand for high-reliability and low-latency connections for smart industrial applications, healthcare, smart transportation, smart grid, entertainment, and media.

One millisecond is the minimal latency offered by 5G, with the restriction that one millisecond is only radio latency. End-users may be more concerned with device-to-device latency, and distance is the most straightforward way to calculate this latency. The resultant longdistance optical transmission in 5G is the sum of the device-to-device latency.

This allows us to compare the current situation to the previous 2G/3G/4G situation.

Fiber transmission latency, according to

OpenSignal's analysis, is meaningless across the whole spectrum of device-to-device latency in the 2G period. This indicates that the total number of latency is calculated by the radio latency.

This percentage has risen to 60% in the 5G era.

Device latency and detailed user experience can be affected by fibre and location transmission.

As a result, it should embrace supplying local services to lower the proportion of transmissions across all of its assets when low 5G latency needs to be better exploited.

Computing technologies will aid the development of mobile edge computing at the IT edge, which can address this need.

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All of these devices would send data directly to the cloud if they didn't use edge computing.

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High Bandwidth

The high bandwidth of 5G is another important feature. Users, on the other hand, would be able to witness more vibrant video and enjoy depth sensitivity at up to 10GB per second. On the company's side, the cost of cloud deployment rises dramatically, and building public network capacity for users is difficult. You must examine the network architecture and determine how traffic will be routed from the midrange cloud to the high-end cloud.

The technological success of 5G networks is aided by the link between 5G and edge computing. When working with the millions of devices connected to 5G networks, edge computing makes 5G conceivable.

All of these devices would send data directly to the cloud if they didn't use edge computing. This will also push the demand for cloud transfer bandwidth to new heights, putting 5G networks to the test.

3

Great Communication

In a typical IoT scenario, a large amount of data might be generated.

Resources are wasted if all data is transmitted to the cloud for processing.

When the data is pre-processed in the middle, the downstream feedback can be swiftly built to complete the IoT system's closed loop.

Simultaneously, scalable data can be combined to form IoT swarm intelligence.

The utilization of terminal computer services is the focal point here. As a result of the preceding study, the following

conclusions can be drawn: 5G support capabilities will become the primary driving force for mobile edge computing development.

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Real-time Performance

Businesses can collect large volumes of real-time data and analyze it to boost productivity and customer experience across a range of applications using 5G and edge computing, enabling them to process and analyze large amounts of data.

Organizations can get closer to the real-time performance of essential applications by doing analysis and processing close to where the data is created.

5

Development of Rising Applied Sciences

The advancement of applied sciences such as artificial intelligence (AI), augmented reality (AR), machine learning (ML), and digital reality (DR) requires extremely rapid connections for information processing at the edge.

These advancements in applied science are significant because they have the potential to revolutionize entire industries and enable endless creativity if new goals can be met.

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5G and edge computing, particularly by bringing computers closer to information, are driving innovation since it allows for the integration of artificial intelligence and seamless machine learning, opening new possibilities for business situations. It also opens the door to IoT possibilities.

As technological and social challenges are minimized, combining 5G with edge computing and its impact on AI, ML, and IoT makes smart cities more viable and provides a foundation for innovation.

Telemedicine is another area where 5G and edge computing can help to eliminate constrained transmission. In addition, industrial automation entails learning from the most efficient and inventive solutions.

Manufacturing may eventually appreciate the value of a well-designed and clever supply chain in increasing efficiency.

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Potential Drawbacks

1 Large Attack Surface

The attack surface will grow when 5G confinement application cases become more common. As the possibilities of a successful attack increase, this appears to be a sensible way to scare the character.

2 Complexity

Companies may try to use technology but fall short of meeting regulatory standards, financial performance, and underlying technical concerns like scope, rate of change, and variability.

3 Modular Ecosystem

Ecosystem communication has become unmanageable as a result of its dynamic nature. As a result, there are numerous options to explore for various budgets and degrees of performance and control.

Enterprise Use Cases Virtual and Augmented Reality

Manufacturing

Employees from various sectors can exchange and use the same physical products, allowing corporate purchasers to benefit from engrained real-time interactions. Smart mirrors can also assist ART employees in changing assembly, maintenance, operation, and referral instructions, allowing them to complete their responsibilities more quickly.

Oil and gas development, food and beverage, and consumer products are all affected by edge computing and 5G. Edge computing can be used in distributed and remote areas.

These locations can use 5G to connect to independent systems. Infrastructure can also be improved to ensure that these locations can manage 5G data needs.

New staff can be trained using augmented reality and virtual reality headsets. You can learn to accomplish a variety of activities and tasks with few errors. In marketing and promotion, 5G edge supports AR and VR, giving potential buyers an intuitive preview of products and services. Users can, for example, take a virtual tour of a real building or location and put on clothing and cosmetics.

Environmental monitoring of food and beverage goods to maintain the freshness of perishable products is another edge computing and 5G deployment. Edge systems can be included in the manufacture of consumer items by adjusting structured production statistics. Using private networks, these edge systems can connect to channel partners.

Smart mirrors can also assist ART employees in changing assembly, maintenance, operation, and referral instructions, allowing them to complete their responsibilities more quickly.

Moving Forward With 5G and Edge Computing From a technological and business standpoint, businesses can begin to comprehend the value and effect of 5G and edge computing.

They can then identify 5G and edge computing issues and possibilities that will assist them in winning or losing.

The development of 5G plans and edge computing at this stage will help ensure that the expected operational circumstances are not only business-specific but also technology-specific. It also enables businesses to leverage successful examples of application and guarantees that technology evolves organically through use.

Data Backups: Critical Part of Cyber Strategy Strategies to Protect Your Data

by Utsav Mishra

W

e live in a data-centric world, and everything around us contains data. Be it the apps we use on our phones, the excel sheets we fill at work; the stats we present during presentations; or the Wikipedia page with a list of awards received by our favourite movies.

Have you ever searched for the perfect school for your kid? When you start searching on the internet, what do you see? You look for all the data of a specific school or various schools and then curate the best amongst them. This world is so data-driven that even the slightest things that we do come back circling to data.

In a world where you can access anything at your fingertips because of smartphones, what can be the biggest loss to someone.

You might have heard people say it often, whether at work or at random places, that their phone's/laptop's memory got corrupted and they lost entire data.

Imagine going to a waterpark with your kids and then suddenly drowning your phone in the swimming pool. If the phone drowns and doesn't start working, what will happen?

You might lose all the data stored in the device. Now that sounds like some serious nightmare.

In such cases, what is the thing that you wish for? The first thing that comes to any sane mind is, "Aah I wish I had backed up that data" or "Thank God I had a data backup".

These are the two most immediate reactions. As we mentioned the term data backup here, you must be curious about it. So let us move ahead now.

What is Data Backup?

The technique of copying data from a primary to a secondary place in order to secure it in the event of a malicious activity, disaster, or accident is known as data backup. Data is the lifeblood of modern businesses, and losing it can result in significant losses and disrupt operations. This is why data backup is essential for all businesses, big and small.

Typically, backup data refers to all data required to perform the workloads on the organization's server. Documents, media files, configuration files, machine images, operating systems, and registry files are all examples of this. In essence, you can save any data that you want to save as backup data.

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Importance of Data Backup The main purpose of the backup is to create a duplicate set of the data that can be retrieved if the main data fails or gets lost. Hardware or software failures, data corruption, or any human-initiated incident such as a hostile attack (virus or malware) or data deletion by mistake can all result in primary data failures.

These backup copies now allow data to be recovered from an earlier point in time, which can help a firm recover quickly after an unplanned event.

To protect against primary data loss or corruption, a copy of the data must be stored on secondary media. A disc storage system, cloud storage container, or tape drive might be as simple as an external drive, or a USB stick can be used for backup. Backup copies 58

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should ideally be created on a regular basis for optimal outcomes. This will help to reduce the amount of data lost between backups. When recovering from a backup, the longer the gap between backup copies, the greater will be the risk of data loss. Multiple copies of this data provide the assurance and flexibility of being able to restore to a point in time where data damage due to malicious attacks has not occurred.

The fundamental purpose of a data backup is to keep a safe archive of your vital information.

It can be classified documents for your business or priceless family photos. You can quickly and relatively effortlessly recover your device from data loss.

Even so, 30% of people have never backed up their data.

This may not appear to be a significant amount until you consider how frequently data is lost: • Every minute, 113 phones are either lost or stolen.

• By the end of this year, it is expected that a hacker will gain access to 40% of small to medium-sized organizations that operate their own network and use the internet for purposes other than e-mail. More than half will be unaware of the attack.

• Each month, one out of every ten PCs is maliciously infected with a virus.

• In the United States, a laptop is stolen every 53 seconds.

A single hard disc won't be adequate as RPO climbs in tandem with demand for your services and data volumes.

Redundancy, a more complex data backup approach, is frequently used in this situation.

Data Backup Strategy Developers have created a slew of programs to help back up your data during the last few decades. To get the most out of the data backup strategy, you must choose the correct option for the size and purpose of your company. The most prevalent data backup solutions are discussed below:

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Cloud Backup Alternatives

Cloud migration has been increasingly popular in recent years, with more businesses than ever turning to cloud providers for data storage. Cloud backups give you the assurance that all of your vital enterprise data is safely stored off-site. They provide additional protection and redundancy, ensuring that data is accessible from anywhere in the event of a calamity.

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Data Backup Software

3

External Hard Disk Drives

Although hardware appliances and external hard drives are typically easier to set up than software, the flexibility and additional features make them a must-have for many firms' data backup plans. You may specify which data and systems you wish to back up, automate the backup process, and assign different categories of data to other devices.

Many firms' backup processes rely heavily on high-capacity external hard drives, especially when paired with archiving software. Users may restore files from an external hard drive using this software, reducing RPO to only a few minutes.

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4

Hardware Appliances

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Removable Data Storage Media

Backup appliances often have a large storage capacity and pre-installed backup software. The appliances are simply installed on the required systems, backup policies are defined, and data is then sent to the storage device. Hardware appliances should be deployed offsite or outside of the local network infrastructure if at all practicable.

Using removable data storage media like USB sticks, DVDs, and Bluray discs is one of the most traditional and straightforward ways to do manual backups. While this may be sufficient for modest operations, higher volumes of data necessitate larger drives, complicating the recovery process.

Furthermore, it would be best if you stored data backups at a secondary place to avoid loss in the event of a disaster or onsite theft.

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What is the 3-2-1 Backup Strategy?

According to the 3-2-1 rule, data should be saved in three copies or versions on two distinct media pieces, one of which is off-site. Let's examine each of the three aspects and the issues they address with an example.

We'll use "Catalogue.jpg" as an example; it is a photograph of your product catalogue for the year 2012 and is stored on your computer. That's just one copy of the file.

You might also have a hard disc that you utilize externally to back up the computer data; if you're a Mac user, it could be a Time Machine drive (and Backblaze loves Time Machine). The file will be backed up on the external hard disc as part of its backup routine. This is a duplicate on a different device or medium. If you also have an online backup solution in addition to the external hard disc. The online backup analyses your machine in real-time and uploads your data to a data center elsewhere. This upload includes the file, which becomes the third copy of your data.

The 3-2-1 method is a fantastic place to start when it comes to backing up your files.

If you consider your files to be investment capital, you'll want to diversify them as much as possible to reduce your risk of disaster.

Liquidity is also necessary; having a local and off-site backup provides you with more backup recovery choices.

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Cybersecurity and Organizations Small businesses are becoming increasingly vulnerable to cyberattacks. Smaller companies have fewer resources to devote to data protection, making them an easier target for cybercriminals. When a hacker compromises just one user, they often get the "keys to the castle."

Ransomware swiftly and secretly gets installed on a victim's device and mounts an extortion attack, demanding a ransom in exchange for access to their data, all with a seemingly harmless click on a link or e-mail attachment. If that person is using a cloud collaboration platform like Google Drive, OneDrive, or Dropbox, the virus can quickly propagate throughout the firm. Now the entire firm is in jeopardy.

In such cases, data backup is the prime solution to protect your business from cyber threats. And this isn't just applicable to small businesses, but we have used it because the case of small businesses can explain this way more clearly.

Conclusion It's all too tempting to put off catastrophe planning until "when you have time," especially when you have more than enough work to do for running your business. Disasters and hackers, unfortunately, don't care if you're prepared or not. Take the time now to set in motion processes that will save you time – and money – in the future.

Data backup is not only limited to being a solution to cyber threats. It is also equally essential for the cases of lost phones or laptops and word-out disk drives. A cloud backup is a great option so is the drive backups.

Choose the perfect backup plan for your business wisely and let all the stress of cyberthreats vanish.

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Customer Service in The Digital Age

Do We Still Need Human Interaction?

by Saipriya Iyer

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ustomer service has been of utmost importance for businesses for a long time, given how critical customers are to help a company reap successful long-term results and distinguish its brand from the competition. What commenced in the form of written communication and telephone conversations to face-to-face interaction has today transformed into a full-fledged, value-driven service portfolio for customers.

Conventional strategies are no longer sufficient to address the changing needs of today's market.

With changing customer behaviour, the stakes are significantly higher, and businesses need to work harder to provide increasingly beneficial yet cost-effective and, to a considerable extent, personalized services to customers.

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In today's world, driven by consistent digitalization, ensuring that customers are happy is more of a challenge than ever. With happier customers comes better trust in the brand and, consequently, more loyalty and advocacy. As per reliable reports, people may be four times more likely to buy a product referred by a known person. There's an 18% increase in loyalty from a referred customer instead of the one obtained from a different method.

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As of today, there are almost 4.4 billion active internet users worldwide, a number that will only serve to increase in the coming years. With a considerable percentage of the global population going online, businesses have access to a wide number of digital customers, paving the way for successful strategies to be coined – such as interacting with customers via live chat, virtually enhancing purchase experiences, and so on. Digitalization has revolutionized customer experience and can have a profound impact on customer behaviour, in turn, impacting the brand value of a business.

Statistics About Companies Adopting Digitization Businesses had been adopting digitization way before the pandemic; however, it cannot be denied that the onset of COVID-19 acted as a tremendous trigger, pushing companies to rapidly scale up the deployment of digital strategies to accelerate their business.

At present, digital transformation is at its peak and has led to the deployment of new business models implementing modern technologies such as machine learning, chatbots, data analytics, and blockchain.

Companies across major end-use sectors have been rapidly integrating IT solutions in their ecosystem, generating new challenges and opening up numerous growth opportunities.

Back in 2021, IDC predicted that 30% of organizations would increase innovation and generate new models to digitize their companies. According to IDC, 60% of enterprise executives are of the opinion that IoT will have a major role to play in their companies' digitalization.

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Gartner had predicted that by 2023, close to 70% of organizations will use value stream management to enhance development and operations pipeline flow, leading to better, faster customer service.

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In addition, the highest growth of digital transformation was expected to be from devices (close to 14%) and enterprise software (approximately 10.8%), owing to companies providing innovative workplace solutions.

InformaTech predicts that AI software revenues may cross USD 100 billion globally by 2025.

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InformaTech predicts that AI software revenues may cross USD 100 billion globally by 2025. Close to 60% of companies may deploy artificial intelligence solutions to help employees in the near term, states Deloitte, while Forrester says that digital transformation investments rose at over 3X the rate of overall IT expenditure.

With speedy internet becoming rather commonplace, more and more companies have been adopting digitization, investing heavily in business intelligence platforms to enhance customer experience.

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In 2021, Flexera claimed that around 37% of IT initiatives undertaken by companies globally focus on improving customer experience.

The software company had also stated that 49% of companies across the globe prioritize cybersecurity when it comes to technology initiatives, while around 54% prioritize digital transformation.

According to a survey of 1,200 mid to large-scale US companies, the average digital transformation budget was pegged at USD 14 million in 2018, while digital transformation expenditure worldwide may cross USD 1.78 trillion in 2022. In addition, IDC claims that around 65% of global GDP may be digitalized by 2022.

With most industrial enterprises and startups having already adopted strong digital transformation strategies and a substantial percentage planning to adopt one soon enough, the digital ecosystem worldwide is set to proliferate at an appreciable rate. As customers form the nucleus of digitalization, businesses are expected to continue the adoption of digital solutions to enhance the customer experience in an increasingly competitive marketplace.

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How Has Pandemic Affected Digitization and Its Adoption?

The impact of the coronavirus pandemic on the adoption of digitization has been overwhelming.

Many companies had strong security and IT mechanisms in place and had already been working to transition to a digital ecosystem. For these establishments, the onset of the pandemic made it easier to transition to a virtual working environment quickly. For many others, especially the ones with rigid legacy systems in place, an aging infrastructure, and bandwidth constraints, the pandemic was a brutal wake-up call to quickly digitalize their business models and create a new ecosystem in place for the future. This rang true in the case of government firms with severe capacity issues and the lack of a mobile-friendly presence. In effect, the pandemic forced several companies to accelerate the adoption of digital solutions, which included the deployment of virtualization and the cloud.

According to a report by Celerity, around 63% of industry leaders claimed that the pandemic prompted them to adopt digital transformation strategies sooner than they had planned. A similar report by IBM states that a mammoth 96% of leaders reported COVID-19 to fast-track their digital transformation plans by around 5.3 years.

One of the biggest changes sparked by the COVID-19 pandemic was observed in the payments industry. With social distancing becoming the norm due to nationwide lockdowns, the online payments sector depicted a meteoric rise, paving its way to becoming one of the fastest-growing markets worldwide.

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Having observed consumer interest in virtual payment models, several companies, even the ones with an originally conventional model, transformed their payment systems into consumer-friendly, digitalized versions.

In essence, the pandemic played a crucial role in speeding up the adoption of digital solutions, as contactless payment volumes witnessed an exceptional rise in demand across retail outlets, pharmacies, grocery stores, departmental stores, vegetable and fruit sellers, recharge vendors, and many others including prominent players across the and EdTech sector.

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the demand for telehealth and online consultations depicted an upsurge as well.

Hospitals and medical establishments raced ahead to embrace digital transformation to monitor the increasing influx of patients. As per McKinsey, during 2020, the use of digital tools for health support by customers saw a rise of 15%, while it was predicted that around 37%of of consumers might very well use telehealth in the future.

In addition, the research firm asserted that around post the pandemic, the use of telehealth increased from 11% to 76%. While it has had devastating effects overall, the pandemic has certainly helped push the implementation of digital tools across several industrial sectors. www.techfastly.com

Importance of Relationships with Consumers As the popular old adage goes, 'The customer is always right'. Well, technically, this need not be true; however, it brings home an important point – customer satisfaction is highly critical for a business to be successful. At the end of the day, retaining consumers for your product/ service is essential if you want the business to make money at all. Establishing strong, loyal relationships with customers, to that end, is one of the most vital strategies companies must adopt.

Building customer relationships ensures increased employee morale, reduced customer attrition, excellent sales, and

high turnover. However, just establishing a liaison with the customer does not produce successful results – maintaining customer relationships is important. To that end, it is critical that companies increase focus on customer relationship management (CRM) as a vital tool. Customer acquisition is important, yes, but customer retention is more critical today.

Having good relationships with customers mandates consistent improvisation in company services. Customer behaviour and expectations change periodically with changing trends and a transforming 73

marketplace. Alongside, continual improvisation is vital so as understand changing consumer needs and fulfill them accordingly. A single negative experience or a seeming lack of concern can completely phase the customer out of the transaction ecosystem and negatively impact the company as well.

According to a survey conducted by PwC a year ago, 1 in 3 customers out of the 15,000 that were surveyed, chose to abandon a good brand after just one bad experience, while close to 92% may completely abandon the business after two negative experiences. In consequence, sour customer relationships can very well kill the brand sooner than one may realize.

A vital point that forms a part of good customer relationship management is paying attention to customer support. Customer feedback about a product/service, no matter how trivial, must be placed on a high pedestal.

At the end of the day, customers want to feel heard, want to feel that they matter. A company that ensures appropriate customer satisfaction has more of a chance of retaining customers than a company that ignores customer feedback.

In today's bustling work culture, paying attention to changing customer needs and behaviour is more important than ever before. Businesses need to adopt suitable CRM software to understand customer requirements and how to fulfill the same effectively while maintaining brand awareness.

As per estimates, using effective customer relationship management tools can help increase sales conversion rates by an astonishing 300%.

How Have Chatbots and Other Services Taken Over Customer Services?

With an increasing number of brands trying to make their presence felt amid a cutthroat marketplace, the landscape of customer service has entirely changed in the last half a decade. Companies across myriad industry verticals are leveraging AI to ensure effective customer support. To that end, chatbots – virtual assistants, have made quite a reputation for themselves by handling multiple customer service pain points at the same time. For instance, chatbots are used today 74

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to resolve customer queries without human intervention, help customers 24/7, and handle multiple customers at once.

These AI-powered bots are suitably developed to use existing information and resources to help resolve customer questions. They are designed to recognize and answer query variations and can also be trained to provide instant responses in various voices and tones.

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Because of their 24X7 availability, chatbots have quickly become a popular channel for customer inquiries. Users can promptly engage with chatbots in a live session and get all their questions resolved without having to meet an actual customer service executive face to face. This also enables customers to get their queries quickly resolved on demand, reducing the load on companies' service teams. In effect, chatbots can take over simple question responses that usually take up 70%80% of customer service representatives' day.

This time can be efficiently spent on resolving a more detailed customer query, leading to proactive customer support.

A vital reason why chatbots are taking over customer support is the financial strain. By installing a chatbot just once, businesses are able to save tons of money by not having to hire numerous customer service personnel.

This comes as a cost-effective solution for understaffed teams in companies.

The increasing proliferation of digitization indicates that the humanizing technology trend is well on its way to becoming mainstream. Take Alexa, for example, the virtual assistant that has probably had more conversations with customers than they may have had with actual people. To that end,

No matter how efficient and knowledgeable a virtual assistant is, it cannot match the convenience and understanding provided by a human customer service representative.

companies are finding a way to revolutionize customer service by adopting digital solutions and making them as personable and empathetic as possible.

Chatbots are thus being carefully programmed to understand the customer's pain points and voice changes and then resolve queries accordingly, in a deeply sympathetic voice that resonates with the brand in question. Chatbots are reshaping the entire dynamics of customer services by discarding redundant traditional messaging platforms and being available round the clock to transform even first-time visitors into permanent customers.

Are Human Interactions Still Needed?

Contrary to popular consensus, digitized tools and virtual assistants may not exactly phaseout actual customer service entirely; human interactions may still be the need of the hour.

In the aftermath of the pandemic, numerous companies turned to computerized customer service platforms and chatbots; however, it has been observed that many users are getting increasingly annoyed at having to communicate with a mechanized voice.

This is because no matter how efficient and knowledgeable a virtual assistant is, it cannot match the convenience and understanding provided by a human customer service representative. Many are of the opinion that bots may have ready-made answers for standardized questions, but they will never be able to fully understand what the customer wants or solve the query the way the customer asks.

As per a survey comprising 2,000 consumers by outsourcing company CGS, almost 40% of British survey respondents claimed that speaking with a human customer service representative was preferable to having to converse with a virtual assistant. The same viewpoint was shared by United States survey respondents, 38% of which wanted companies to bring back human customer service.

The biggest reason, however, for the retention of human customer service is the fact that users still want to feel needed, understood, and valued. Personalization is important, and so is active listening and empathetic communication that will help a company understand their customers well. Human interactions not only resolve the query in hand, but also help establish a long-term, personal relationship with users, thereby helping to increase customer satisfaction by up to 20% or more. It is more than likely that customer service in the digital age may be characterized by a mixture of efficient bots and human staff, harnessing the best of both and helping businesses retain as many consumers as possible.

Despite convenient online access and reliability, close to 83% of consumers claim that they prefer human interaction as opposed to digital assistants, according to the Global Consumer Pulse Research study from Accenture Strategy.

Edge and Cloud Computing

Can They Coexist Peacefully?

by Toulika Das Edge computing is an emerging trend in modern computing that is developing in tandem with cloud computing. The link between edge computing and cloud computing may be somewhat complex.

However, in many cases, integrating cloud computing and edge computing simultaneously might result in the most outstanding overall performance output.

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Conversations on the link between cloud computing and edge computing incline us to depict the cloud and Edge as opposing architectures that must be either/or. So here's a look at whether edge computing will eventually replace the cloud or whether something a little more similar to coexistence will occur.

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Edge Computing Vs. Cloud Computing - The Main Differences The primary distinction between edge computing and cloud computing is where workloads are housed. Applications and data in a traditional cloud are kept in massive data centres situated within the network of a public cloud vendor. On the other hand, workloads in an edge architecture are housed in a "closer" to end-users from the network's perspective than in a regular data centre.

It is crucial to note that the idea of Edge might become a bit confusing since there are so many varied approaches to designing an edge architecture. For example, an edge ecosystem can sometimes run straight on end-user devices. However, in many others, it seems to be a classic data centre inhabited by traditional servers, which are located closer

to end customers than typical cloud data centres.

From such an architectural standpoint, cloud computing is more straightforward. Although teams may utilize different cloud areas and zones to host workloads, all public cloud platforms rely on traditional data centres that are comparably far - in terms of networking from end-users.

Although there are significant distinctions between cloud and edge computing, the cloud and the edge complement one other rather than contend. We may better understand this topic by first studying the advantages of cloud and edge computing individually.

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Advantages of

Advantages of

Edge Computing

Cloud Computing

Organizations that deploy IoT devices or detectors that gather vast volumes of data at the Edge will be able to leverage their edge devices to do localized data processing, resulting in quicker reaction times. Miller urged any firm that has use cases with low demand latency, such as Industrial IoT or cognitive applications, should investigate the usage of edge computing to complement their computer architecture.

He adds that applications that leverage 5G technology are also well-suited to edge computing.

According to Michael McCarthy, assistant professor of information systems, cloud providers will grow more significant in the coming years, not less. "For upgrades and security fixes, code will need to be redeployed to the edge, while edge components will need to communicate with cloud components for apps that simply cannot function on edge alone."

Miller anticipates that the number of edge computing applications will continue to grow as software architects discover the benefits of lower latency in cognitive and industrial IoT applications.

McCarthy believes that computers in the cloud will always be quicker and more competent than those on the periphery.

They will also benefit from more fantastic large databases and more robust networks. In contrast, machines on the Edge will always have fewer resources than those in the cloud.

According to Ed Fox, CTO of IT telecom business MetTel, the cloud is incredibly versatile in computation and prolonged storage applications.

In addition, it is engineered to manage surges effortlessly. While the Edge may not give the same level of elasticity as the cloud, it might add to a company's maintenance and operations workload. "It takes extra effort to keep these edges running smoothly and design high availability and business continuity scenarios." According to Fox, other significant edge disadvantages include increased network operation and data governance complexities.

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Top Companies To Invest in Edge Computing So, how does this link between Edge and cloud infrastructure present itself? It's a blend of instances from the present and the upcoming future. Some significant companies made the shift from cloud to edge platforms.

from the Edge with various workloads. It enables strong AI deduction skills in IBM Visual Insights and IBM Visual Inspector specialists who use the POWER 9 CPU.

IBM

Few companies have the technological infrastructure to support edge computing as well as Google, thanks to its worldwide network and reach. Many people already have a Google gadget at home. Google has a linked home product line for edge computing. It also offers cloud computing services to manage edge data, most notably through its Cloud IoT Core service.

IBM has a great partnership with major corporations and provides an IoT solution for organizational asset management, infrastructure solutions, and system engineering. In addition, the firm advertises a competitive advantage in cloud computing by allowing enterprises in the telecoms, retail, and car industries to operate facilities at the network's Edge, utilizing edge computing for workstations.

IBM has been working on Edge Analytics, which deals with deploying ML models, Neural Nets, and Data Analytics at the Edge. It has also created IBM Watson Studio, a platform for data scientists to graphically build neural networks and experiment with training data using the NVIDIA Tesla V100 GPU and a selected deep learning framework.

IBM Edge Architecture aids in the safe management of all linked edge computing devices. IBM Maximo Visual Inspection, through deep learning, makes artificial intelligence more approachable to business users. It analyses data at the Edge, allowing faster responses to sophisticated analytics.

The software is simple to implement into edge devices and operates efficiently. IBM Power Systems & AI Solutions is an IT network that employs AI solutions to give market insights

Google

Google runs analytics and AI at the Edge using Edge TPU technology.

Furthermore, Google's other AI cloud services suit its edge computing offerings.

Google Cloud IoT Edge is a software that leverages edge computing to extend Google Cloud's data processing and machine learning capabilities. It also enables its usage on gateways, cameras, and end devices, enabling applications to be quicker, secure, and dependable. Google Coral is essentially a unique machine learning platform designed for use in edge applications. It enables users to create their gadgets by utilizing local AI. This platform also contributes to hardware acceleration on all edge devices.

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Microsoft

Dell

Microsoft is a dominant cloud computing firm, but unlike other big companies like Amazon and Google, Microsoft has many edge computing patents in its inventory, the majority of which outline solutions to industry difficulties.

Dell has made significant investments in edge computing. Dell EMC provides edgecomputing management and orchestration capabilities via OpenManage Mobile.

Microsoft has several edge computing products in addition to its patents. Azure IoT Edge, for example, is a fully managed solution developed by Microsoft that allows customers to install cloud workloads, AI models, business logic, and the Internet of Things (IoT) on edge devices using standard containers. In addition, technologies like Azure Defender are specifically created and updated regularly to guarantee end-to-end threat prevention on edge servers.

Dell EMC categorizes its edge computing gear into three groups.

THE ENTERPRISE EDGE portfolio (which features the VEP460 Open uCPE platform), THE MOBILE EDGE PORTFOLIO (which contains cloud-enabled hardware at mobile or distant sites) and THE IOT EDGE PORTFOLIO (which includes Edge Gateways for manufacturers, shops, and digital cities) are among them.

Azure Defender are specifically created and updated regularly to guarantee end-to-end threat prevention on edge servers.

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Amazon Amazon is a prominent cloud computing provider, so it's not unexpected that the corporation is also a leader in Edge computing, despite possessing less number of patents relating to the technology.

AWS wavelength is an AWS framework that enables developers to create applications for cellphones with extremely low latency. The edge computing infrastructure for telecommunication carriers uses standard AWS computing and storage capacities at the Edge of 5G networks.

AWS Storage Gateway is a kind of a hybrid storage solution that provides limitless cloud storage.

Consumers use Storage Gateway to simplify storage management and save expenditures.

This includes migrating backups to the cloud, utilizing on-site file sharing supported by cloud storage, and providing low latency access to AWS data for several on-site applications.

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How Can Edge Computing & Cloud Computing Coexist Peacefully?

There is an argument that edge computing is a supplement to cloud computing rather than its imminent replacement. Edge will not be able to completely replace cloud computing because there will still be a requirement for centralized processing for quite some time.

On the other hand, Edge computing is a reaction to cloud computing, a method of accounting for some of its drawbacks. This strategy is more effective when cloud computing is employed on the one hand, and computational power is also used on the edges using an edge computing approach for devices where this is helpful.

Edge computing is used to process data that is timesensitive, whereas cloud computing is used to handle data that is not essentially time-sensitive.

Aside from latency, edge computing is preferable over cloud computing in remote areas when access to a centralized site is restricted or non-existent. These places need local storage, akin to a small data centre, and edge computing is the ideal answer for this.

Edge computing is also advantageous to intelligent and specialized devices. While these gadgets are similar to PCs, they are not standard computer devices with various functionalities. These clever customized computer devices respond to specified machines in a specific way.

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However, in particular, businesses that need quick reactions, this specialization becomes a disadvantage for edge computing.

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What Does The Future of Edge and Cloud Computing Look Like?

In many scenarios, using both cloud and Edge simultaneously makes sense. For example, cloud data centres may host applications that do not demand the low latency and high dependability of edge technology, whereas edge infrastructure can handle those who do.

According to one research study released in October 2021 by MarketsandMarkets, the edge computing industry will increase from $36.5 billion in 2021 to $87.3 billion by 2026, with a compound yearly growth rate of 19 per cent over those five years.

Enterprises may exploit the scalability and simplicity of deployment of cloud environments while still attaining high-performance targets that cloud data centres can't always fulfil owing to network latency difficulties by combining cloud and Edge. However, this is not to argue that you must always employ cloud and Edge together. It is undoubtedly feasible to host apps or data in the cloud without simultaneously maintaining an edge environment. Edge can also be used without a cloud environment; however, this is less frequent.

Integrating cloud computing and edge computing can result in outstanding overall performance results. The only significant disadvantage is that managing a cloud and an edge environment simultaneously can be a bit difficult.

To sum it up, edge computing is similar to science fiction, becoming a reality with more opportunities and development. Not only will your company face a new generation of success, but employing the Edge will help you operate your organization more effectively, generate more great inventions at a faster pace, and gain more benefits from affiliations.

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Intel Vision 2022

What Does The Future of Edge Computing Hold?

by Aftab Alam

Intel is a worldwide technology giant that develops game-changing products that improve people's lives all around the world. It is constantly working to improve the design and production of semiconductors to meet its customers' needs. Intel liberates data's transformative power by putting intelligence in the cloud, network, edge, and every computing device in between.

Intel Vision 2022 shows how the company's silicon, software, and services are transforming areas like education, banking, manufacturing, medical, transportation, and defence.

Intel showed off new hardware, software, and services as part of its first annual Intel Vision event. It also showed how these technologies and the ecosystem can help customers now and in the future. Real-world examples show that the benefits include increased business results and insights, the reduced total cost of ownership, faster time to market and value, and a positive global effect.

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This is the most dynamic worldwide market in which we have ever found ourselves.

WPat Gelsinger, CEO of Intel, said, "Today's organizations face complex and interrelated difficulties, and their success depends on adopting and using cuttingedge technologies and infrastructure.

We're happy to discuss how we're leveraging size, resources, and silicon, software, and services to drive digital transformations for our clients and partners."

Transformative Power for Digital Transformations from New Silicon and Software From a fully hybrid workforce to whole new immersive experiences that can only be realized through the power of artificial intelligence, pervasive computing, pervasive connectivity, and cloud-to-edge infrastructure, the demand for semiconductors is at an all-time high. In addition, organizations confront increasing challenges regarding supply chain management, security, sustainability, and the ability to react to new workloads, all at the same time. New hardware, software, and services from the cloud to edge to the client are being introduced by Intel to help solve these difficulties.

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The Following Announcements Have Been Made Until Now: When it comes to AI training, Gaudi processors are known for their ability to help customers train more while paying less. They've made a significant improvement in deep learning processing with Habana Gaudi2. Synapse AI, the software stack that drives Habana Gaudi2 and Greco AI accelerators, has been published, benefiting end-users from their performance and efficiency. For core vision and NLP workloads, Gaudi2 delivers two times greater AI training performance compared to A100-based products in the industry.

This generation of Intel Xeon Scalable processors sets the bar high for current computing power. The 4th generation Intel Xeon Scalable processors (codenamed Sapphire Rapids) are now shipping in early quantities from Intel. In the remaining months of this year, there will be a significant increase in the number of new SKUs that are released. On Intel's 4th Generation Xeon Scalable CPUs, DDR5, PCI Express Gen 5, and CXL 1.1 are all supported. Additionally, new integrated accelerators give up to 30 times the performance of the prior generation for AI workloads compared to the previous generation. New capabilities for vRAN deployments can bring up to two times the capacity improvements for telecom networks, as well. A significant increase in the amount of memory bandwidth accessible to the processor will be made possible by Intel Xeon processors with high bandwidth memory (HBM), code-named Sapphire Rapids.

An open-source AI solution kit program from

Intel and Accenture, called Project Apollo, was launched with the goal of making artificial intelligence (AI) more accessible in onpremises, cloud, and edge environments.

According to the latest information available, the first Project Apollo kits will be available over the next several months.

In-Place Processing Units (IPUs) are playing an important role in their preparations for the future data centre. As part of Intel's IPU plan, which stretches all the way through 2026, a brand-new FPGA + Intel architectural platform has been introduced (with the code name Hot Springs Canyon), as well as an ASIC that has been given the moniker Mount Morgan (MMG). Because IPUs are dedicated devices with acceleration built for infrastructure computing, organizations may finish tasks and solve problems faster.

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A single GPU-based computer that can power a cloud-based media transcoding, visual graphics, and inference solution: Intel's Arctic Sound-M (ATS-M) data centre GPU is the first discrete GPU in the industry to incorporate an AV1 hardware encoder. This innovation was made possible by Arctic Sound-M. With its 150 trillion operations per second objective, the ATS-M is a powerful GPU that can handle a wide range of tasks (TOPS). With the help of oneAPI, ATS-M developers will be able to quickly design for the open software stack.

ATS-M will be offered in two form factors and more than a dozen system designs from Dell Technologies, Supermicro, Inspur, and H3C. It 96

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will go into production in the third quarter of 2022.

In-vehicle hybrid use of the latest Intel Core HX processors: This year, Intel released its final CPUs in the 12th generation, which are dubbed "Core HX." The Intel Core i9-12900HX CPU is the world's best mobile workstation platform4 for professionals that require maximum performance and flexibility in a hybrid environment. It has up to 16 cores and clock speeds of up to 5 GHz. Project Endgame, Intel's first concept demonstration of its software infrastructure www.techfastly.com

program, shows that users demand the freedom to access computational resources whenever and wherever they need them. This software infrastructure layer enables devices to use the computing resources of other devices in the network to deliver a continuous compute service that is always available, has low latency, and is constant. There are a number of ways in which a user's experience is enhanced by using greater graphics processing power from a more powerful machine. This year, Intel will begin beta testing the first iterations of Project Endgame in preparation for a full release later this year.

It was also revealed that Intel is taking early measures toward enabling service models across the ecosystem. With the launch of Intel's On Demand service offering, organizations can satisfy the needs of evolving workloads, product sustainability, and the potential for scaling systems near the data. Intel developed a new consumption business model that enables customers to fit their infrastructure with their business needs and requirements, which is now offered through select partners: HPE GreenLake, Lenovo TruScale, and PhoenixNAP's Bare Metal Cloud.

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Making a Difference for the Betterment of Our World You get a feeling of exactly how powerful Intel's portfolio is and how big of an influence it can have on the world when you witness real-world examples of how Intel's vast variety of products perform together. This is because these examples take place in the real world.

Highlights Include: Aurora Supercomputer Using high-performance computers to find solutions to some of the world's most intractable issues: At Argonne National Laboratories, the Aurora supercomputer, which is driven by an Intel Xeon CPU and given the code name Sapphire Rapids with High Bandwidth Memory (HBM), and the Intel data centre GPU, which is given the code name Ponte Vecchio, are on track to deliver a peak performance of 2 exaflops. To begin the conference, Rick Stevens, Argonne Director of Computing, Environment, and Life Science, showed the Aurora supercomputer installed for the first time and discussed how it will help solve some of humanity's most complex problems, such as better climate predictions and the discovery of new cancer treatments while making exascale accessible for more research and development and innovation.

Confidentiality in Computing When it comes to using regulated data to train and create neural networks, multinational organizations must take into account a variety of factors. An AI solution that allows Bosch to train its neural networks privately in the public cloud was developed in collaboration with Intel as part of a research project. Using Intel® Software Guard Extensions available on 3rd Gen Intel® Xeon® Scalable processors,

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Bosch Corporate Research has developed a confidential AI platform.

Intel® Smart Edge and Intel® Xeon® D Processor Private wireless networks can help farmers become self-sufficient in their operations. In the future, farmers will benefit from intelligent edge solutions that can enhance yields and operational efficiency while addressing labour shortages and human error. Additionally, data analytics can help farmers improve yields and crop health while requiring fewer resources.

An autonomous farming solution developed

by Blue White Robotics transforms a grower's existing equipment into a fleet of autonomous vehicles that are managed via the internet.

Using Intel® Smart Edge and Intel® Xeon® D processors, as well as shared spectrum and edge computing, Blue White Robotics created a scalable system that can be used on any farm, anywhere, to build a private wireless network.

Fully Autonomous Store Shopping Experience The pandemic has affected the way people shop, with many preferring businesses with touchless or self-checkout alternatives rather than those that require human interaction.

In an effort to create a frictionless shopping

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experience, Nourish + Bloom Market embraced automation without sacrificing employees.

UST, a leading transformation solutions firm and Intel worked together to tap into the combined technical knowledge to produce this. It will require breakthroughs like a nextgeneration self-checkout, computer vision technology, and a fully autonomous store shopping experience.

To ensure a brighter future for future generations, Intel collaborates with organizations like the Hidden Genius Project and Autodesk on projects like Intel's AI Festival and the Hidden Genius Project's engagement with Autodesk to further reduce its direct and indirect greenhouse gas emissions. Intel Vision has a lot more to share, and this is just the beginning.

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