Optimized SPIN in Wireless Sensor Network

IJSRD - International Journal for Scientific Research & Development| Vol. 4, Issue 05, 2016 | ISSN (online): 2321-0613

Optimized SPIN in Wireless Sensor Network Neha Khurana Assistant Professor SAL Institute of Research & Engineering, Ahmedabad Abstract— The popularity of Wireless Sensor Network (WSN) has increased tremendously in recent times. WSN has the potential to connect the physical world with the virtual world by forming a network of sensor nodes. In a sensor network the sensor nodes sense the data within their sensing range. Each node has limited energy which is used in transmitting and receiving the data thus energy preservation is most important for the survival of sensor networks for longer period time. Many routing protocols in WSN are used for the same purpose. In WSN, SPIN is a data centric routing protocol which efficiently propagates information among sensor nodes in an energy constrained mode. SPIN uses metadata negotiation to eliminate the redundant data. In this paper we proposed a mechanism to Optimize the SPIN Routing Protocol. The main objective of this paper is to use the metadata information while advertising, to reduce the energy consumption by the nodes in transmitting and receiving the data. We have implemented Basic SPIN and proposed Optimized SPIN protocols using MATLAB. After implementation we found that in Optimized SPIN, the number of dead nodes are 50% lesser than the existing SPIN protocol.

Key words: Wireless Sensor Networks, Metadata, SPIN

or moving while receiving data or waiting for a query response. While moving, a sink should continuously update its topological position information in the sensor nodes to maintain paths. This may require large signalling overhead, resulting in excessive energy consumption.

The basic block diagram of a wireless sensor node is presented in Figure 1. This figure is composed of four basic components: a sensing unit, a computing unit, a communication unit and a power unit. The communication part of sensor node uses wireless communication devices, to be able to receive and forward data using a wireless link.

The WSNs are used to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants, at different locations. The main applications of WSN are tracking, controlling and maintaining. Sensor nodes may be used in different area just like medical applications, military areas, commercial and industrial applications, home automations, real time applications, logistics, outdoor monitoring and much more. The list of its applications is endless.

I. INTRODUCTION Wireless Sensor Network has recently been extensively deployed and researched. In recent time communication has played an important role in everybody’s life. If communication is without wire, then it is just like a boon for everyone. Wireless Sensor Network is a network which consists of application based tiny devices known as sensor nodes without using wires. All the devices are autonomous and are not controlled by human users. Those devices are much more constrained in terms of battery life and processing power the major elements of WSN are the sensor nodes and the base stations. Sensor nodes are the collection of small devices with the task of measuring the physical data of its surrounding. Base stations are the powerful devices in charge of collecting data from the nodes and forwarding control information from the users. In fact, they can be abstracted as the “sensing cells” and the “brain” of the network, respectively. A sensor node has limited computational power and its lifetime is based on the lifetime of an onboard battery and therefore power consumption is always an important consideration.

The unique feature of sensor network is the cooperative effort of sensor nodes. The sensed data by sensor nodes is conveyed through the sensor network of wireless links by multiple hops and gathered in such a way that can be perceived as the interface between sensor networks and users. Multiple sensor networks can be integrated into a larger network through the Internet or direct links.

WSN is having a characteristic of sending data from one sensor node via another by coordinating with each other to a base station or sinks, these sinks may be stationary

Fig. 1: Architecture of Wireless Sensor Node For a wireless network, the devices operating on battery try to pursue the energy efficiency heuristically by reducing the energy they consumed, while maintaining acceptable performance of certain tasks. However, for multihop routing, which is typical for ad hoc and sensor networks, this is not the optimal strategy. In this paper we will focus on the energy consumed by the SPIN routing protocol and proposed an Optimized SPIN for reducing the energy consumed by the nodes. The rest of the paper is organized as follows: Section 2 presents related work. In Section 3, we present our system model. Section 4 elaborates the results and discussions while Section 5 concludes the paper.

II. RELATED WORK Here we are focusing on Data centric routing protocols. In data centric routing the sink sends queries to certain regions and waits for data from the sensor nodes which locates in the selected region, since data is being requested through queries. Attribute based naming is necessary to specify the properties of data. The algorithm we are focusing on is SPIN

All rights reserved by www.ijsrd.com

1073

Optimized SPIN in Wireless Sensor Network (IJSRD/Vol. 4/Issue 05/2016/269)

(Sensor Protocol for Information via Negotiation). The SPIN family of protocols works upon two basic ideas.  First, to operate efficiently and to conserve energy, sensor applications need to communicate with each other about the data that they already have and the data they still need to obtain. Exchanging sensor data may be an expensive network operation, but exchanging data about sensor data need not be.  Second, nodes in a network must monitor and adapt to changes in their own energy resources to extend the operating lifetime of the system.

In [6], authors proposed a new technique which was working on the problem of data inaccessibility and blind forwarding problem. On that basis four protocols were defined. Two basic protocols were SPIN-PP and SPIN-BC, both of them were handling the above problems with the consideration that there will not be any packet loss. Two modified versions of above protocols were also defined, that were SPIN-EC, an energy conserving version of SPIN-PP and other is SPIN-RL, a reliable version of SPIN-BC which recovers losses in transmission. SPIN-PP or SPIN-1 is a negotiation process which is based upon 3 way hand shaking process for point to point, which contains three stages:  Data Broadcasting stage  Data Requesting stage  Data Transmission phase SPIN-EC or SPIN-2 is a SPIN-PP with low energy threshold, In this approach when a node observes that its energy is approaching a low energy threshold it adapts by reducing participation (i.e. less participation will provide less energy consumption by a node). SPIN-BC is also based upon 3-way handshaking protocol for broadcast media, it also contains three categories just like SPIN-PP. SPIN-RL is a SPIN-BC for lossy networks. In this approach it provides reliability in data sending in broadcasting. If any node does not receive the data then after a span of time it again requests for the same data.

SPIN-IT: A Data Centric Routing Protocol for Image Retrieval has been presented in [7]. In this paper, authors proposed a protocol which considers image as data and by using spin techniques data received will be chosen as optimal sources. Example, Based on robustness or perceived longevity of route record. In this route record, each data is being Rout-Reply packet header and source closest to the requesting node is chosen for data transfer.

In [8], authors proposed a Modified SPIN for Wireless Sensor Networks. Authors suggested that data must be circulated towards the sink node. In this protocol a new phase is added in existing phases to find distance of each sensor node in the network from sink to sensor node and vice versa, i.e. the more number of hops in between increases the distance between sink and nodes, that phase is called distance discovery, i.e. total phases in modified spin are:  Distance Discovery  Negotiation  Data Transmission Adaptable Protocol for Time Critical Information Dissemination via Negotiation in large Scale Wireless Sensor Network is proposed in [9]. The authors suggested that SPIN can be modified with the property of clustering for saving time and energy. It was named as Cluster Based

SPIN (CBS). The rotation of Cluster head leads to a balanced energy consumption of all nodes and hence to a larger lifetime of network. Rest of the procedure will be performed by cluster heads.

In [10], authors compared the energy consumption used by LEACH and SPIN routing protocols. They used 50 nodes and simulated for 2 min and concluded that spin fares much better than the LEACH protocol in terms of energy consumption. In SPIN and LEACH protocols the LEACH protocol has limited amount of energy but it has more energy consumption as compared to SPIN just because of cluster head selection (CHs) and the other reason of consuming more energy is it follows 4 steps to transmit the data which are Advertisement phase, Cluster setup phase, Schedule creation phase and Data transmission phase. In all the phases the most energy consumes in the rotation of cluster heads as it changes randomly its role of cluster head.

But in SPIN there is no concept of cluster heads so energy is being saved. SPIN protocol uses the concept of metadata with negotiation i.e. number of dead nodes in SPIN is comparatively less than in LEACH. Authors in [11] discussed the existing protocols SPIN, SPIN-1 and Modified SPIN. They proposed a new protocol named EEM-SPIN after facing some problems in Modified SPIN. The problem in M-SPIN was that while sending the data only in the direction toward sink, there is the possibility that some of the nodes may be used several times for sending the data, so those nodes may lead to dead nodes due to low energy. So resolving this problem author proposed a new protocol which is an enhanced version of M-SPIN. They introduced the concept of clusters and dynamic cluster head selection in M-SPIN to reduce the problem faced. As in dynamic cluster head selection the cluster heads are chosen randomly i.e. the nodes which were used for forwarding the data repeatedly may save their energy.

III. SPIN ROUTING PROTOCOL In data-centric protocols, when the source sensors send their data to the sink, intermediate sensors can perform some form of aggregation on the data originating from multiple source sensors and send the aggregated data toward the sink.

This process can result in energy savings because of less transmission required to send the data from the sources to the sink. SPIN routing protocol is a routing protocol which comes under the category of data centric routing protocols.

SPIN protocol is a protocol which helps the sensor nodes to pass on the information from one to another by negotiating with each other. Every node in SPIN negotiates with each other for the data to save its energy. SPIN protocol uses the concept of metadata. The meta-data negotiations are used to eliminate the transmission of redundant data throughout the network but one thing which is important while sending the metadata that the size of metadata must be lesser than the absorption capacity of the communication sensor. [12] A family of adaptive protocols called SPIN which is designed to address the deficiencies of classic flooding by negotiation and resource adaptation.

SPIN protocol was designed to improve classic flooding protocols and overcome the problems they may cause, for example implosion and overlap. The SPIN protocols are resource aware and resource adaptive. The sensors running

All rights reserved by www.ijsrd.com

1074

Optimized SPIN in Wireless Sensor Network (IJSRD/Vol. 4/Issue 05/2016/269)

the SPIN protocols are able to compute the energy consumption required to send, receive and compute data over the network. Thus, they can make informed decisions for efficient use of their own resources.

The SPIN protocols are based on two key mechanisms namely negotiation and resource adaptation [14]. SPIN enables the sensors to negotiate with each other before any data dissemination can occur in order to avoid discrepancies and redundant information in the network.

Sensor nodes usually generate significant redundant data. So, to reduce the number of transmission, similar packets from multiple nodes can be aggregated. Data aggregation is the combination of data from different sources according to a certain aggregation function.

(a) Node B responds by sending a request to Node A (b): After receiving the requested data (c): Node B then sends out advertisements to its neighbours (d): Who in turn send requests back to B (e–f)?

Fig. 2: Working of SPIN protocol SPIN has three types of messages i.e. ADV, REQ and DATA. Before transmitting the DATA message, the sensor nodes broadcasts an ADV packet containing a descriptor i.e. Meta data as shown in figure 2. If a neighbour is interested in the data, it sends a REQ packet to the originator for the DATA and DATA is sent to its neighbour without considering the type of data or what kind of data is required. By repeating the same the interested sensor nodes in the entire sensor network gets a copy of DATA [19].

The main working of SPIN routing protocol is based on the negotiation in sending the information from one node to another. Each node tries to preserve its energy and negotiate with another so that other can consume its energy and it can increase its life time. As figure 2 describes that the initiator node sends an ADV packet to each of its neighbour nodes, if any of them responds by sending a REQ packet, it then send the DATA packet to the requester node.

This procedure is repeated till the information moves from sender node to receiver node or to base station or sink.

IV. PROPOSED WORK As we have studied in Basic SPIN methodology, it uses the concept of metadata. Any of the nodes, who want to send its data will first, advertises its ADV packet then request packet REQ is being sent by the interested nodes who wants to receive the data. After that DATA packet is sent by the initiator node and then the receiver node accepts that data according to the need, rest of it will be discarded, i.e. the receiver node dissipated its energy in receiving the data and discarding the useless data which causes high amount of energy loss, but what if only a part of data is required to the requester node. In the above case that node has to use its

high energy for receiving the DATA, but if the portioned data is sent to the requester node then the total amount of energy consumed will be less than that of previous one.

(a) Node A sends Advertise Packet (ADV) to B. (b) Node B sends Request Packet (REQ) to A. (c) Node A sends complete Data Packet (DATA) to B. Fig. 3: Packet Transfer in Basic SPIN Protocol Figure 3, shows that in Basic SPIN sender node sends complete data packet to the requester node irrespective of its need. If only a part of data is required by the requested node then sender may send a portion of data which will reduce the energy consumption of sender and receiver nodes by 1/10 part (approximately).

(a) Node A Advertise Packet (ADV) having Meta-Data to B. (b) Node B sends Request Packet (REQ) having selected data request (2 & 5) to A. (c) Node A sends only requested data (2 & 5) in Data Packet DATA to B. Fig. 4: Packet Transfer in Optimized SPIN Protocol Figure 4, shows that if a node (say B) needs only a part of data (say 2 & 5), it can send the request for that particular data only and can receive only the requested part of data. If we send the data on the basis of Basic SPIN (Figure 3) then full data packet has to be send to requester node. After receiving complete data, receiver node will accept only the needed data and rest it will discard, which will consume more energy in sending and receiving respectively but if we develop such a methodology in which only selective data will be sent to the requester node, then it will obviously reduce the energy consumed by sender and receiver both. By using this method the energy dissipated by a node that is sending DATA packet will be reduced as well as the receiver node who is accepting the DATA packet will also use less amount of energy in receiving the data packet.

That may lead to less dead nodes and survivability of the sensor network will be increased.

V. RESULTS AND DISCUSSION The purposed Optimized SPIN and existing Basic SPIN have been implemented using MATLAB. The goal of the implementation is to demonstrate the advantages of Optimized SPIN over Basic SPIN. Assumptions for the implementation: 1) Sensor Network has 100 nodes, which are randomly deployed over the field.

All rights reserved by www.ijsrd.com

1075

Optimized SPIN in Wireless Sensor Network (IJSRD/Vol. 4/Issue 05/2016/269)

2) Sink is assumed in centre of the field.

3) Initial energy of each sensor node is assumed as 0.5 units.

4) The energy dissipated of a node in Advertising is assumed as EAD=0.00005 for both Existing Basic SPIN and Optimized SPIN. 5) The energy dissipated of a node in transmitting the data is assumed as:  In Basic SPIN: EAD=0.00000005.  In Optimized SPIN: EAD=0.0000000005.

6) The energy dissipated of a node in receiving the data is assumed as:  In existing SPIN: ERX=0.00005.  In Optimized SPIN: ERX=0.000005.

In Optimized SPIN Energy consumption is 10 times lesser than that of Existing Basic SPIN because in Optimized SPIN we are going to send a part of data that is requested by the sensor node.

After taking these assumptions we have implemented both Basic SPIN and Optimized SPIN. The goal of this implementation is just to show, how Optimized SPIN reduces the number of dead nodes in the field after the whole transmission. Figure 5, shows that, in existing Basic SPIN when we work on 100 nodes after the whole transmission no of dead nodes lies in between the range of 40-50 but in Figure 6, proposed Optimized SPIN shows that, after working on the same number of nodes when the transmission ends the total number of dead nodes got reduced up to 50%. So this implementation shows that in Optimized SPIN sensor network will survive more than the Basic SPIN.

Fig. 6: Optimized SPIN, No of dead nodes: 26 Figure 7, shows that, as the number of simulation runs increases the number of dead nodes in existing Basic SPIN lies in between the range 40-60, but for the same number of simulation runs the number of dead nodes in the network lies in between the range of 20-40, which is approximately just half of Basic SPIN.

Fig. 7: Comparison Graph in between Basic SPIN and Optimized SPIN VI. CONCLUSION In this paper, we have implemented our proposed protocol in MATLAB. One major advantage of this protocol is its simplicity. Each node needs only specified information in the whole data so why to waste energy in sending and receiving unwanted data. By the implementation result of Basic SPIN and Optimized SPIN it can be concluded that Optimized SPIN becomes more energy efficient in comparison to existing SPIN. It also reduces the redundant data packet due to the metadata negotiation. By using Optimized SPIN dead nodes are approx 50% lesser than Basic SPIN, so the network will survive more Optimized SPIN. REFERENCES

Fig. 5: Existing Basic SPIN, No of dead nodes: 49

[1] F. L. Lewis, “WIRELESS SENSOR NETWORKS”, Smart Environments: Technologies, Protocols and Applications, pp 1-2, 2004.

[2] K, Akkaya, M. Younis, “A survey on Routing Protocols for Wireless Sensor Networks”, Proceedings of Elsevier Adhoc Networks Journal,Vol 3, pp. 325-349, 2005.

[3] I. F. Akyilidiz, M. C. Vuran, O. Akan, W. Su, “Wireless Sensor Networks: A survey Revisited”, Proceedings of Computer Networks journal(Elsevier Science), Vol 45, No 3, 2004.

[4] KAZWM SOHRABY, “Wireless Sensor Technolgy, Technology, Protocols, and Application”, Wiley Inter science, 2005, pp: 50-68.

[5] Ning Xu, “A Survey of Sensor Network Applications”, www.courses.cs.tamu.edu/rabi/cpsc617/resources/senso r%20nw-survey.pdf [6] Joanna Kulik, Wendi Rabiner And Hari Balkrishnan, “Adaptive Protocols for Information Dissemination in Wireless Networks” 8, 169–185, 2002, ©2002 Kluwer Academic Publishers, Manufactured in The Netherlands.

[7] Edward Woodrow & Wendi Heinzelman, “SPIN-IT A Data Centric Routing Protocol for Image Retrieval in Wireless Networks”, International Conference on Image

All rights reserved by www.ijsrd.com

1076

Optimized SPIN in Wireless Sensor Network (IJSRD/Vol. 4/Issue 05/2016/269)

Processing, 2002, ISSN: 1522-4880, ISBN: 0-78037622-6, Pages: 913-916, vol.3, DOI:10.1109/ICIP. 2002.1039121.

[8] Zeenat Rehna, Sarbani Roy, Nandini Mukherjee, “A Modified SPIN for Wireless Sensor Network”, IEEE, Vol 4, pp-1-4, 2011.

[9] M. Tabibzadadeh, M. Sarram & M. Ghasemzadeh, “Adaptable Protocol for Time Critical Information Dissemination via Negotiation in Large scale Wireless Sensor Network”, 978-0-7695-3925-6/09 $26.00 ©2009 IEEE, DOI: 10.1109/ICCEE.2009.201.

[10] Geetu & Sonia Juneja, “Performance Analysis of SPIN and LEACH Routing Protocol in WSN”, International Journal Of Computational Engineering Research (ijceronline.com) Vol. 2 Issue. 5, ISSN 22503005(online) September, 2012, Page 1179-1185.

[11] K. Karthikeyan & M.Kavitha, “Comparative Analysis of Data Centric Routing Protocols for Wireless Sensor Networks”, International Journal of Scientific and Research Publications, Volume 3, Issue 1, January 2013 1, ISSN 2250-3153.

[12] Jafar Amiri, Masoud Sabaei, bahman Soltaninasab, “ A new Energy Efficient Data gathering Aproarch in wireless Sensor Networks”, In: Scientific Research, Vol 2, pp-1-12,2012.

[13] Arvind Kumar and Chanpreet Singh, “Comparison of AODV ,DSR and TCRP protocols for Routing algorithms in WSN for IEEE 802.15.4 standard Based devices”, International Journal of Computer Science and Telecommunications, Vol 2,pp-1-7,2011.

[14] Edward Woodrow & Wendi Heinzelman, “SPIN-IT A Data Centric Routing Protocol for Image Retrieval in Wireless Networks”, International Conference on Image Processing, 2002, ISSN: 1522-4880, ISBN: 0-78037622-6, Pages: 913 – 916,vol.3,DOI:10.1109/ICIP.2002.1039121.

[15] Robin Singh Bhadoria & Deka Ganesh Chandra, “Competent Routing protocol in Wireless Sensor Networks”, 2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing, 978-14673-2925-5/12/$31.00 ©2012 IEEE. [16] Munish Bhardwaj, Dinesh Kumar Kotary & Surender Soni, “Comparative Analysis Of Energy Efficient Routing Protocol For Wireless Sensor Network”, Special Issue of International Journal of Computer Applications (0975 – 8887) on Wireless Communication and Mobile Networks, No.14. Jan, 2012.

[17] John M. McQuillan, Ira Richer & Eric C. Rosen, “An Overview of The New Routing Algorithm for The ARPANET”, Proceedings of ACM SIGCOMM Computer Communication Review - Special twentyfifth anniversary issue, Volume 25 Issue 1, Jan. 1995, Pages 54–60, ACM New York, NY, USA, DOI:10.1145/205447.205453.

[18] Wei Ye, John Heidemann & Deborah Estrin, “An Energy-Efficient MAC Protocol for Wireless Sensor Networks”, Proceedings of USC/ISI TECHNICAL REPORT ISI-TR-543.

[19] Nidhi Batra, Anuj Jain & Surender Dhiman, “An Optimized Energy Efficient Routing Algorithm For Wireless Sensor Network”, International Journal of

Innovative Technology & Creative Engineering (ISSN:2045-8711), VOL.1 NO.5MAY 2011.

[20] Munish Bhardwaj, Dinesh Kumar Kotary & Surender Soni, “Comparative Analysis Of Energy Efficient Routing Protocol For Wireless Sensor Network”, Special Issue of International Journal of Computer Applications (0975–8887) on Wireless Communication and Mobile Networks, No.14. Jan, 2012.

[21] G. Nivetha, “Energy Optimization Routing Techniques In Wireless Sensor Networks”, Volume 2, Issue 7, July 2012 ISSN: 2277 128X, © 2012, IJARCSSE. [22] Luwei Jing & Feng Liu “Energy Saving Routing Algorithm Based on SPIN Protocol in WSN”, 978-161284-881-5/11/$26.00 ©2011 IEEE. [23] Joy Iong-Zong Chen & Lu-Tsou Yeh “Environments Aware for Prolonging the Lifetime of Sensor Nodes Deployed in WSNs”, Proceedings of Engineering, 2012, 4, 100-106, DOI:10.4236/eng.2012.42013 Published Online February, 2012.

[24] Arslan Munir & Ann Gordon-Ross “Optimization Approaches in Wireless Sensor Networks”, Chapter 13 of book "Sustainable Wireless Sensor Networks", ISBN 978-953-307-297-5, Published: December 14, 2010 under CC BY-NC-SA 3.0 license, DOI: 10.5772/13093.

[25] A.H. Azni, Madihah Mohd Saudi, Azreen Azman & Ariff Syah Johari “Performance Analysis of Routing Protocol for WSN Using Data Centric Approach”, International Journal of Electrical and Electronics Engineering, Volume 2, No 2.pp 66-69.

All rights reserved by www.ijsrd.com

1077