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NOVEMBER 2017

Inside: Connect the physical with the digital p3 Best practices for industrial Cloud computing p6 Core technologies make edge-intelligence possible p10

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PRODUCTIVITY & BEST PRACTICES: EDITOR’S COLUMN Kevin Parker Senior Contributing Editor

Workforce education becomes an essential task Five essential competencies for the digital era identified

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t its recent user conference, the always thoughtful management of Emerson Automation Solutions discussed work’s changing nature.

The U.S. manufacturing sector experienced 4.0% productivity growth from 1990 to 2000, and 4.7% from 2000 to 2007. Analyses of productivity growth statistics can be highly speculative. At the time, however, experts and media credited computerization for these productivity gains.

Since then, productivity growth has stagnated at about 1.5%. Yet computerization has continued apace. If digitalization was the cause of productivity growth in the 1990s and in the first decade of the 21st century, what caused the subsequent productivity growth slowdown?

Computers today are communication devices in support of the coordination of work, as much as they are anything else. If the network is the computer, then advances depend on integration, and just 50 years into the computer revolution we’re faced with a multi-layered installed base. In fact, integration seems to be the constraining challenge. Moving forward, while remaining cognizant of legacy systems, has proved complex and daunting.

Essential competencies Another kind of “installed base” is the industrial work force involved. In the last 40 years, many kinds of work were transformed, and quantified, as computerization supported work-process reengineering.

At the conference, Emerson tackled the topic during a briefing on “essential competencies for an empowered digital workforce.”

“The past 30 years have brought fantastic advances in the manufacturing sector, including greater operating efficiencies enabled by automation. But the incremental gains are diminishing,” Mike Train, executive president, Emerson Automation Solutions, said.

The silver lining will come with an emerging generation of technologies able to revitalize productivity gain, as in the former era. However, the work force is the essential www.controleng.com/IIoT

piece. “The readiness and capacity for change is limited,” said Train.

Emerson is expanding its service offerings to help fill the gap. What industry needs, Emerson said, is an increased focus on education and upskilling along with improved organizational workflows to effectively leverage their technology investments. An analysis commissioned

by Emerson of the organization behaviors of Top Quartile industry performers indicated five essential competencies for the digital era.

Automated workflow allow focus on exceptions requiring human intervention. Analytics and embedded expertise reduce complexity. Workforce upskilling empowers personnel to acquire knowledge and experience more quickly. Mobility provides access to information regardless of location. Change management accelerates institutionalization of operational best practices.

Expectations expanding “Process control has been digitalized already,” said Peter Zornio, chief technology officer, Emerson Automation Solutions. “Users expect real-time information, embedded expertise, and a closed-loop system. We can now do the same thing for other type operations, including reliability, safety, and energy, for example. In the new era, core production workers will be focused on collaboration, interpretation, and analytics, rather than data collection and reporting.”

Where are we at this moment? One last quotation taken from the user conference provides a hint: “Wireless is arguably the most impactful technology for industrial manufacturers since the introduction of digital instrumentation more than three decades ago,” said Bob Karschnia, vice president and general manager, wireless, Emerson Automation Solutions. “Industrial wireless combined with smart sensors are the foundation to support cloud-based applications, remote monitoring, and other IIoT programs over the next decade.” IIoT IIoT For Engineers

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IIoT IN THE NEWS

IIoT platforms released and updated Suppliers package IIoT capabilities as a solution

K

epware released the KEPServerEX version 6.3 industrial connectivity platform. Key enhancements include improved create, read, update, and delete (CRUD) functionality for the configuration API, time sync functionality for drivers with electronic flow measurement (EFM) capabilities, a Keyence KV Ethernet driver, and remote project loading via the ThingWorx IoT Platform.

“This release will give users more control over their projects, even when connecting remotely. With version 6.3 we’ve also added a new driver to our industry-leading portfolio.” said Jeff Bates, Kepware product manager.

Along with the Keyence KV Ethernet driver, KEPServerEX version 6.3 also includes: Enhanced CRUD functionality for the configuration API: Configuration API users can now remotely trigger project saves for any instance of KEPServerEX, create an object with a child hierarchy in a single transaction, and create multiple objects in a single transaction. Configuration API users can also now make bulk changes to the configuration and trigger ATG, enabling faster changes on larger projects. KEPServerEX version 6.3 enables users to interact less with the local configuration and easily write common code for objects in disparate projects.

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Time sync functionality for drivers with EFM capabilities: Users can now set a custom time sync threshold for any driver with EFM capabilities and ensure no synchronization occurs unless a specific deviation limit is exceeded. OnPoll, the new time sync method included in version 6.3, also lets users configure time synchronization to occur only after an EFM poll. This reduces network traffic and provides users more control over time synchronization.

Remote project loading: Taking advantage of the existing security of the ThingWorx native client interface in KEPServerEX, users can now import a KEPServerEX project from a local file store and push the project down to any connected instance of KEPServerEX. Users can easily adjust network settings and deploy KEPServerEX projects remotely—while managing all of their machine instances from a single ThingWorx platform interface.

Industrial software platform reintroduced

Schneider Electric announced EcoStruxure Industrial Software Platform, an integrated, modular software suite that delivers functionality to address operational and business imperatives in industrial and infrastructure markets.

According to Schneider, the platform is a “proven solution capability for engineering, planning and operations, asset performance, and control and information management.” With more than 2 million software licenses deployed at 100,000+ sites worldwide, processing 10+ trillion daily transactions spanning 20+ billion operating parameters, the platform operates at a scale to support complex and mission-critical industrial operations.

The platform is hardware and systems agnostic and can be deployed in a scaled, modular fashion.

The platform includes a wide range of commercial options (Subscription, SaaS, Perpetual) and deployment flexibility (on-premise, cloud-based) for all its available functionality. This lowers total cost of ownership without compromising risk, data security, and performance requirements.

The domain-specific functionality of the industrial software platform enables business excellence: supports engineering, operations, asset management and people enablement. The information management, business process knowledge and decision support capability available across the modules of the platform are specific to industry problems.

They allow companies to upgrade competencies, document operational experience, and develop the next generation workforce. IIoT www.controleng.com/IIoT

WORKPLACE TRANSFORMATION

Connect the physical with the digital Leaders say, don’t let culture impede technology progress

By Dr. Keshab Panda

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ridging the divide between the physical and the digital worlds, the Industrial Internet of Things (IIoT) transforms how companies function and how work gets done, based on gains in sensor and microcontroller technology, connectivity, and analytics. These emerging technologies are also conceptualized as Industrie 4.0.

Businesses focus on operational excellence to streamline and tighten production processes. Six Sigma

techniques support these efforts. IIoT gives these companies an opportunity to go beyond Six Sigma, fool-proofing many activities and processes related to operational efficiency.

These trends see support in a survey from L&T Technology Services and ARC Advisory Group conducted at this year’s ARC Forum. Half the survey respondents were with large corporations having more than $10 billion in revenue. According to the survey results, 57% of business leaders and organizations embrace IIoT for operations-related work. Key focus areas for

IIoT are to enable augmented operations, human-robot collaboration, advanced digital-product development, data-driven control of operations, and predictive maintenance.

Early adopter feedback shows that the transition to an IIoT ecosystem depends on employee initiative. The survey also highlights that 42% of business leaders feel that organizational culture acts as an impendent to IIoT adoption. Capital expenditure concerns are also prevalent.

While about 40% of organizations said their companies are at the pilot

The positive impact of IIoT can be short-term operational efficiency, but it also can have a long-term influence on resource optimization, product design, and automation. All graphics courtesy L&T Technology Services www.controleng.com/IIoT

IIoT For Engineers

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WORKPLACE TRANSFORMATION

An IIoT-enabled framework streamlines and integrates a value chain, including with applications in predictive maintenance, plant performance optimization, and asset tracking.

An IIoT system includes sensors/chips, edge gateway, IoT platform, cloud services, and data analytics. Bringing together these disparate elements enables the system to be run

While conventional IIoT frameworks are available, a scalable and longterm approach integrates IT, OT, and BT. While IT deals with increasingly large databases, OT is about physical devices and processes, and BT is about business software applications.

Two typical characteristics of any IIoT-based system include information processing on a 24x7 basis and real-time constraints imposed by the environment.

A comprehensive IIoT architecture might include sensors, for detecting events or changes; edge gateways that aggregate and filter sensor data; IIoT Cloud-enabled platforms, including smart-signal aggregators and modelling algorithms; Big Data analytics, including machine learning, artificial intelligence, augmented reality, data store, and security. The entire system is meant to run as a managed service.

In addition, technology firms add IIoT value by offering managed engineering services as a key building block of the IIoT system. Managed services comprise round-the-clock remote monitoring, predictive maintenance using data analytics, and value engineering. Thus, a new kind of build-operate-manage model will increasingly become the paradigm for technology providers.

as a managed service.

Case study examples stage of evaluating IIoT, 31% said they’re already in discussions with partners and ready for gains on firstmover advantage. Predictive analytics and Integrated IIoT are key those adopting IIoT.

Given the need Let’s take a step back to discuss what really makes up an IIoT architecture. In IIoT systems, industrial assets and operations technology (OT) such

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as materials, machines, and plant control systems, interconnect with information systems and technology (IT). Also connected are users, along with the enterprise business processes and technology (BT). Once connectivity and system data flow between OTIT and BT is accomplished, data can be aggregated and analytics applied.

As insights are gained, smart decisionmaking leads to intelligent industrialoperation and business models.

Business-process management and enterprise-resources planning integrate systems and processes to a degree. The comprehensive structure enabled by IIoT takes further steps. An IIoT-enabled framework can integrate processes starting from the productdevelopment stage through manufacturing to supply chains. Possible capabilities include data-driven inventory, remote asset testing and inspection, data-driven quality control, remote www.controleng.com/IIoT

service, additive parts manufacturing, augmented operations, human-robot collaboration, and advanced digitalproduct development.

While IIoT is in the early stages of adoption, inspirational narratives abound. For instance, a global construction company faced critical business challenges managing field assets and equipment. This was addressed using IIoT technologies that in turn enabled development of a remote asset performance management framework. The framework covers 30,000 assets across 500 asset types. It delivered an estimated 12% improvement in asset utilization. Ontime asset availability will likely lower overall costs as well.

Services supporting the solution implementation included sensor identification, gateway selection, sensor-gateway commissioning, and on-boarding. Such an IIoT system generates six gigabytes of data per day, deriving data intelligence from about 2,500 nodes.

In another instance, a consumergoods manufacturer addressed the operational disruptions caused by frequent compressor failures in its manufacturing plants using IIoT technologies. The system used predictive analytics to proactively estimate time to failure, using anomaly indicators including temperature, current, vibration, and other parameters. The model works at more than 70% inaccuracy and is estimated to result in annual savings of about $500,000.

The impact to come According to a report by McKinsey & Co. Inc, IIoT will have a potential economic impact of up to $6.2 trillion by 2025. McKinsey lists IIoT as one of the key technologies capable of economic transformation.

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IIoT platforms will be a critical success factor for goods makers and services providers. Industries that leverage IIoT to integrate data, machines, and people will see impacts on productivity, efficiency, and operations. IIoT

Dr. Keshab Panda is CEO and managing director, L&T Technology Services.

THE DIGITAL WORKPLACE

Best practices for industrial Cloud computing delineated Match organizational preferences with the relevant technology requirements

by Melissa Topp

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ntegrating the Industrial Internet of Things (IIoT) into traditional supervisory control and data acquisition (SCADA) and human-machine interfaces scenarios delivers multiple benefits.

Increased scalability follows from secure access to multiple locations via cloud platforms, including the popular Microsoft Azure. Hardware obsolescence can be alleviated, as the “heavy lifting” of processor-intensive analysis can be off-loaded. Connectivity is enhanced, as increasing numbers of devices communicate via IIoT transport protocols.

However, without the ability to connect devices from behind firewalls and to publish data securely to IIoT-integrated applications, organizations may miss out on the promise of advanced analytics via Cloud computing. If your organization is considering an IIoT integration strategy, the answers to the following questions highlight some best practices.

1. Does your organization

already have existing IoT/cloudready hardware?

Some organizations planned for IIoT’s emergence, to ensure machinery electronics and discrete devices in production facilities can transfer

One benefit of Internet-based automation is that it allows centralization of disparate operations, and for expertise to be more easily brought to bear at remote locations. All graphics courtesy: Iconics

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data to a selected cloud service. For instance, a manufacturer may have updated assembly machines with units equipped for more advanced networking. This works well for companies that can afford such retrofitting, but might not be the most cost-effective means of ensuring IIoT connectivity.

Legacy industrial machinery can be connected to an IIoT infrastructure.

However, some add-on hardware connection options often prove, comparatively speaking, cost-prohibitive. That’s where the concept of IoT gateway devices comes in.

IIoT gateways are lightweight devices that act as a bridge between on-premise communications networks and cloud services, at a fraction of the cost of an equipment retrofit. These edge devices provide “southbound” data connectivity to end devices, completely on-premises. A device also provides a “northbound” communication path for connectivity between itself and the cloud.

IIoT gateways incorporate strict security requirements. They serve as the delivery mechanism between the data generated and stored on-premise and that shared with the outside world.

Intel, through its IoT Solutions Alliance program, supports original-design manufacturers with advanced security features such as unique hardware IDs, www.controleng.com/IIoT

secure booting, whitelisting, and disabling of onboard peripherals, such as USB and com ports. Edge management is of equal concern when considering IIoT gateways, as they require remote management once online and are registered with a preferred cloud service.

Needed security configuration and other features are incorporated in IIoT gateway hardware integrated with comprehensive IIoT software solutions.

2. Do you already have a

preferred cloud-services vendor?

Decisions about preferred cloudservices providers might already have been made at your organization, based on on-premise computer, server, and operating system preferences, as well as those for network communication protocols and other factors. Many industrial users rely on Microsoft Azure, while others use Amazon Web Services (AWS) or Google Cloud Platform. These are not the only cloud service options, although they are the biggest. Many others are available, depending on location, each with its own strengths and weaknesses.

For organizations that have not selected a provider, consider the following: What is the pricing structure? Is it easy to understand, with no possible hidden fees?

What is the comparative computing power? How many processing nodes are available at any given time?

What type of database integration is offered—SQL or otherwise? What types of network integration are included—load balancing, DNS, VPN, or another type?

What are the provided storage limits? What are the archiving, sowww.controleng.com/IIoT

In important industries, communications among on-premise machinery and networks with cloud services involve numerous industry protocols, including OPC UA and Modbus.

called “cold storage,” abilities and costs?

Where are the data centers located? Will there be anticipated latency due to distance? How will that effect connected user experience?

Equally important is how well a Cloud-services vendor works with existing or planned IIoT devices and software solutions. Selecting solutions that embrace open standards can help. Ensuring immediate interoperability is an important first step in the best practices for industrial cloud computing.

3. Does your organization prefer specific communication protocols, both for internal use and pub/sub-based?

In important industries, southbound communications between on-premise machinery and networks with cloud services involve

a number of industry protocols, including: OPC Classic specifications are based on Microsoft Windows technology, using COM/DCOM (Distributed Component Object Model) for data exchange between software components. The specifications cover real-time data access (DA), historical data access (HDA), alarms and events (A/E), XML data access (XML-DA), and data exchange (DX), complex data, security, and batch.

OPC Unified Architecture (OPC UA) is an open standard for exchanging information in a rich, object-oriented, and secure way. It provides a platform-independent means for mapping and exchanging real-time information while remaining compatible with the OPC Classic specification.

Modbus is an open communication protocol widely used by IIoT For Engineers

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THE DIGITAL WORKPLACE

many manufacturers throughout multiple industries. The protocol can cover serial lines (Modbus RTU and Modbus ASCII) as well as Ethernet (Modbus TCP).

Simple Network Management Protocol (SNMP) allows devices to expose useful information to other connected devices. Almost all traditional IT devices can handle SNMP requests.

BACnet is the most widely used open communications standard in the building automation industry.

Some organizations might use a proprietary communications method, either in unison with one of the industry standard protocols or exclusively.

Northbound communications involve additional protocols, with the need for high security levels and often using a pub/sub mechanism.

These protocols include: Advanced Message Queuing Protocol (AMQP) provides flowcontrolled, message-oriented communication with built-in options for message-delivery guarantees. Authentication and encryption is based on popular Internet authentication and data-security protocols such as Simple Authentication and Security Layer (SASL) and Transport Layer Security (TLS). AMQP, optimized for messaging between devices, supports read-and-write functionality for command and control or industrial-automation equipment.

Message Queuing Telemetry Transport (MQTT) was created for SCADA environments and related networks, using pub/sub to minimize payloads and overhead with application-specific, custom JavaScript Object Notation (JSON) or binary formats. Widely accepted in IT departments worldwide, MQTT has

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many open-source examples coded in multiple popular programming languages. MQTT is recommended when network bandwidth is a concern and should always be used in tandem with a secure communication method such as TLS. Hyper Text Transfer Protocol Secure (HTTPS) was designed to serve requests and responses in a computing model for Web-page communication. It can more easily traverse firewalls without the need for specific IT policies that handle server request messages and return responses in the form of resources such as HTML files, content, and completion status details.

Representational State Transfer (REST)/JSON provides a stateless means for IoT-friendly information access. It leverages the HTTP transport protocol to deliver data, typically using JSON, which is a flexible, lightweight format like XML, to define its presentation.

When considering IIoT hardware devices and accompanying software solutions, consider both your organization’s southbound and northbound communication requirements.

4. What additional functionality is needed for the industrial cloud-based solution?

By this point, it may be known what new equipment is needed to connect electronic assets to the cloud, who the preferred cloudservices provider will be, and what communication protocols are considered most important.

Cloud connectivity initially may have been considered to secure the benefits of increased scalability with ensured security, reduced hardware obsolescence, and expanded

connectivity. Additional value can be obtained via IIoT connectivity.

This includes connected applications that are provided through a Cloud-services provider, which take customer data at the edge and use it for mobile visualization or analysis.

Examples include energy management or fault detection and diagnosis, rapid data historian storage and retrieval.

Some IIoT gateway software solutions provide seamless integration for these types of applications.

Off-the-shelf SCADA and other type interfaces, analytics, and data historians can connect to a cloud-services provider, subscribing to an “IIoT Hub” from where these applications can ingest the provided data. One possible use case is energy monitoring, where IIoT gateway software running on typical IIoT gateway hardware can connect to popular energy, gas, or water meters for secure, real-time infrastructure monitoring and timely analytics. Another use case is innovative fault detection and diagnostics, where the IIoT software suite can alert personnel of actions to prevent equipment failures or excessive energy use.

Cloud-based computing options, like other emergent technologies, will continue to evolve. A combined IIoT-integrated hardware and software solution delivers value in the forms of equipment monitoring, predictive maintenance, and operational efficiency. Cognizance of suggested best practices can lead to more informed decisions for any organization’s cloud integration plans. IIoT Melissa Topp is senior director of global marketing at ICONICS (www.iconics.com) www.controleng.com/IIoT

Announcing the World’s Most Advanced Communication Chips for the Industrial Internet of Things...

netX 90: Slave Applications

netX 4000: Controller Class Applications

Built-in Security:

Designed for the IIoT:

• Secure boot and cryptography Encryption via SSL/TLS for HTTPS, OPC UA, MQTT, VPN

• Industrial IoT ready OPC UA and MQTT to connect devices to cloud and IT services

• IEC 62443 compatible Enables layered security for Defense-in-Depth design

• Future proof Flexibly adapts by software to emerging standards such as TSN

• Built-in diagnostics Monitor operating conditions for predictive analysis

• Scalable SoC platform Standalone or companion chip applications

• Multiple processors Logical separation of communication and application tasks

• Multiprotocol capability Pre-certified firmware for all popular Industrial Ethernets and Fieldbuses

• Partitioned design Restricts software access to on-chip peripherals on either side • Ten-year availability

• Embedded application Feature-rich set of standard and industry-related peripherals • Best-in-class real-time Supports deterministic, real-time networking

©2017 Hilscher North America, Inc. All trademarks are the properties of their respective companies.

Learn more from Hilscher: call 1.630.505.5301 email: info@hilscher.us or visit www.hilscher.com, www.netIOT.com

THE IIoT LEXICON

Core technologies make edge-intelligence possible Development environments combine device management, connectivity, Cloud, and analytics

By Kurt Au

A

s the Industrial Internet of Things (IIoT) evolves it’s impacted by the same integration challenges as previous automation generations. Besides changing requirements, many different hardware and software technologies and applications apply. However, today, with open standards, these diverse elements can be melded together to deliver solutions.

In IIoT product and application development, developers’ goals may include: Support heterogeneous sensors and actuators via the Internet.

Integrate heterogeneous wired and wireless connectivity protocols, including Modbus, LoRa, Sigfox, Wi-Fi, Bluetooth, and others.

Port original software to different hardware, including MCU, x86/ARM CPU, GPU, and others, and operating systems that include Microsoft Windows, Linux Distributions, mbed OS, Android, and others.

Connect cloud services that might include WISE-PaaS, Microsoft Azure, IBM Bluemix, and others.

Maintain data ownership and integrity and understand its implications for security and privacy.

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Quickly develop robust applications.

Deploy, update, upgrade, and maintain large numbers of devices and services.

Transform Big Data into valuable business information.

Thus, an IIoT product or solution must meet challenges related to sensors, connectivity, security, Cloud

‘

Emerging architectures help companies develop complex IIoT infrastructures in an integrated ecosystem

’

services, storage, device hardware, device maintenance, edge/Cloud analytics, system integration, application development, and so on. The first challenge many companies face is migrating to an IoT application while balancing design time, timeto-market, and risk.

Anatomy of a network IoT data can be large in volume.

Applications typically have real-time requirements. Transmitting massive amounts of raw data puts a load on

network resources. Often it is more efficient to process data near its source and send only the valuable fraction to a Cloud center.

Edge computing is a distributed information technology (IT) architecture in which client data is processed at the periphery of the network, as close to the originating source as possible. Time-sensitive data in edge computing may be processed at the point of origin by an intelligent device or sent to an intermediary server located in close geographical proximity. Data that is less timesensitive can be sent to the Cloud for historical analysis, Big Data analytics, and long-term storage.

Companies must have the means to manage the edge-computing paradigm, whether the solution be referred to as an infrastructure, architecture, platform, or server. What Advantech calls its edge intelligence server (EIS) solution enables local IIoT networks to allow edge intelligence to maximize energy efficiency, reduce privacy threats, promote ease of implementation and modularization, and minimize latencies.

IIoT software platform services are based on three key components: the IIoT node, edge-Intelligence server, and Cloud services. The following describes some technology choices any supplier or using enterprise must make in developing its platform. www.controleng.com/IIoT

An IIoT software platform includes IIoT nodes, edge-intelligence server, and cloud services. Graphic images courtesy: Advantech

For edge-device development, “southbound” sensing-device connectivity must handle diverse sensing protocols, such as Modbus, OPC, BACnet, and Wireless IP/NonIP. These protocols can be handled by plug-in modules that process sensor data, data normalization, and communications.

The solution then handles the “northbound” Cloud connectivity and intelligence facilities using the microservice container paradigm to modularize the different Cloud connections and enable device management. Similarly, intelligence facilities also adopt the microservice container architecture to support the data ingestion workload, such as data preprocessing and cleaning.

Perhaps most valuable of all is the on-demand, real-time analytics service that extracts pre-set data features, in www.controleng.com/IIoT

real time, as data is generated. A predictive maintenance and quality capability serves as a proof-of-concept for edge field prediction.

Using companies extend this framework to develop analytic or predictive-maintenance modules via the architecture’s open standard, based on the ubiquitous MQTT communications protocol and the modularizing Docker container technology.

Other technologies, like RESTful API, MQTT, and Node-RED, facilitate drag-and-drop application development. Node-RED and the configuration utility make it easy to implement custom applications. Moreover, well-documented SDK-with-MQTT sample code and the RESTful API interface allow advanced developers to fulfill high-level requirements.

The last component is Cloud services, with SSL/TLS communications and Intel Security both on the edge device and for Cloud. The data service can provide the PostgreSQL DB and Mongo NoSQL DB as standard offerings, and supports a standard integration interface with a wide range of data processing and storage products. The dashboard website serves as the IoT application user interface, and displays information via browser or mobile device through visualization facilities such as Azure Power BI or Tableau.

At end of day, a platform provides a marketplace for sourcing diverse IoT software utilities, providing pure Cloud solutions such as database, dashboard, and machinelearning tools.

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THE IIoT LEXICON

Further explication Now let’s look a little more closely at some of the technologies previously mentioned.

MQTT is a simple, lightweight publish/subscribe messaging protocol used for constrained devices and low-bandwidth, high-latency, or unreliable networks. The service publishes its capability and data to an MQTT broker and subscribes to specific topics for input interfaces.

A RESTful API defines a set of functions that developers use to perform requests and receive responses via HTTP protocols, such as GET and POST. Because RESTful APIs use HTTP as a transport, they can be used by practically any programming language and are easy to test. It’s a requirement of

a RESTful API that the client and server are coupled loosely and remain independent of each other, allowing either client or server to be coded in any language and improved upon at will, which leads to system longevity and ease of evolution.

The RESTful API specifies what it can provide and how it can be used, and requires that details such as query parameters, response format, request limitations, public use/API keys, methods (GET/POST/ PUT/DELETE), language support, callback usage, HTTPS support, and resource representations should all be self-descriptive.

The properties impacted by the constraints of the RESTful architectural style include:

Component interactions can be the dominant factor in user-perceived performance and network efficiency.

Scalability to support large numbers of components and interactions among components.

The simplicity of a uniform interface.

Modifiability of components to meet changing needs, even while the application is running.

Visibility of communication between components by service agent.

Portability of components by moving program code with the data.

Resistance to failure at the system level despite failures of components, connectors, or data.

Edge computing is a distributed IT architecture in which client data is processed at the network periphery, as close to the originating source as possible.

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www.controleng.com/IIoT

A microservice architecture pattern allows a designer to split the application into sets of smaller, interconnected services instead of having a single monolithic application. A service typically implements distinct features or functionalities, such as connectivity management, vertical application, or other. Each microservice is a mini-application with its own architecture, including business logic along with various adapters.

Containerization is an OS-level virtualization method for deploying and running distributed applications without launching an entire virtual machine (VM) for each application.

Instead, multiple isolated subsystems, called containers, run on one control host and access a single kernel. Containers share the same OS kernel as the host and are usually more efficient than VMs, either of which requires a separate OS instance.

A Docker container wraps up a piece of software in an independent subsystem, complete with file system and everything it needs to run: code, runtime, system tools, system libraries, and anything that may be installed on a server. This guarantees that it always runs the same, regardless of environment.

Containers hold the components necessary to run the desired application, such as files, environment variables, and libraries. The host OS also constrains the container’s access to physical resources—such as CPU and memory—so one container cannot consume all of a host’s physical resources.

Node-RED is available as open source, and is implemented by the IBM Emerging Technology organization. It includes a browser-based flow editor that easily wires flows www.controleng.com/IIoT

together using the wide range of nodes in the palette. Flows can then be deployed to runtime with a single click. The flows created in Node-RED are stored using JSON, and can be imported and exported for sharing with others. It can be run at the edge of the network or in the cloud. The node package manager ecosystem is used to extend the palette of nodes available, enabling connections to new devices and services.

Freeboard provides simple, realtime visualization of key performance indicators. This tool opens up many possibilities for IoT projects because it’s simple, affordable, open source, and ready for extension. Customers can get started for free and then when it is time to ramp up, they can select a plan that’s right for them.

Architecture alignment An architecture of the type under discussion can be classified into five category layers. Each is implemented as its own microservice, using an MQTT broker as the communication bus. All microservices interface with other microservices or clients. At runtime, each instance is a Docker container. This makes it easy to deploy distinct experiences for specific users, devices, or special-use cases.

Containerization is an OS-level virtualization method for deploying and running distributed applications.

1. The bottom layer of the architecture is the sensor network connectivity layer. Wired sensors support various types, including supervisory control and data acquisition (SCADA), Modbus, and OPCUA. The network connectivity layer collects data, manages sensor hubs,

translates sensor protocols to the MQTT protocol, then passes data to the MQTT communication bus.

2. The SDK layer provides software services such as EIS RESTful API, HDD Fault Prediction Algorithm Service, and so on. Developers call these services through RESTful API or MQTT. Users add their own services, such as Machine Learning Platform, Data Base engine, and so on.

3. A flow-based layer has NodeRED as the data-flow design engine, plus add-ons such as SUSI API, WSN, and HDD prediction nodes.

Users design logic paths via simple drag-and-drop operations in a graphical environment.

4.The management and presentation UI interface layer. A Webmin for system administration and IoT connection configuration uses the Node-RED-UI for presenting IoT/sensor data.

5.The Cloud layer may be preinstalled, as for example, with the WISE-Agent connected to WISEPaaS/RMM Cloud Server.

Concluding observations A flexible and scalable hardware/ software architecture helps companies develop complex IoT infrastructure in an integrated ecosystem that serves different vertical markets.

Such an architecture can be customized, combining several software services; it is then installed on different hardware depending on requirements. IIoT

Kurt Au is a product manager in the Advantech Embedded IoT Group.

IIoT For Engineers

NOVEMBER 2017

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