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    • ISSN: 2278 – 1323 International Journal of Advanced Research in Computer Engineering & Technology Volume 1, Issue 5, July 2012 An Improved Approach in Clustering Algorithm for Load Balancing in Wireless Sensor Networks J S Rauthan1, S Mishra2 1 Department of Computer Science & Engineering, B T Kumaon Institute of Technology, Dwarahat, Almora, India E-mail: jsrauthan1@gmail.com 2 Professor, Department Of Computer Science & Engineering, B T Kumaon Institute of Technology, Dwarahat, Almora, India E-mail: skmishra1@gmail.comAbstract: Wireless sensor networks represent environment so replacement or recharging ofthe next generation of sensing machines and battery is not quite possible. Energy consumptionstructures. Inherent limited energy resource is the in transmission is directly proportional to theone of the limitations of wireless sensor nodes. In square of the distance between transmitter andorder to distribute the energy dissipated throughout receiver.the wireless sensor network, data load of the Communications being the major energysensor nodes must be balanced. Clustering is one consuming process, design of data centric wirelessof the key mechanisms for load balancing. sensor networks [1] [2] [3] [4] focus on energyClustering algorithms may result in some clusters efficient data gathering. Clustering [1] of nodes isthat have more members than other clusters in the a scalable and energy efficient process for wirelessnetwork and uneven cluster sizes negatively affect sensor networks. In conventional clustering,the load balancing in the network. In our proposed network is divided into small group of nodes calledwork we improve a cluster algorithm for load cluster. One node from each cluster is selected as abalancing in clusters. Efficiency of WSNs cluster head [1, 3]. All the remaining nodes in themeasured by the total distance between nodes to cluster send their data to their respective clusterthe base station and data amount that has is head. Cluster head aggregate the data and sends totransfer. Cluster–Head which is totally responsible the base station. This scheme works far better thanfor the creating cluster and cluster nodes may direct transmission but network depends onaffect the performance of the cluster. The purposed lifetime of cluster head and cluster head consumesalgorithm we choose a Master Node and vice more energy than other nodes and may die early.master node for regions and sub regions. To find Low Energy Adaptive Cluster Hierarchy (LEACH)out the master node we partition the region and [5] suggests rotation of role of cluster head amongfind out the centered of region, by which we select nodes randomly. A node will be a cluster head forthe master node. For every partitioned region again a round and after which re-clustering is done withportioned if required and much like depend on a new cluster head for each cluster. Every node hasmaster node and nodes in that partitioned area. Our the possibility of being a cluster head. Becausepurposed algorithm we can find the better lifetime cluster had selection is done randomly, energy loadand energy efficiency. balancing is achieved among the sensor nodes in the network.Keywords: Wireless Sensor Networks, Leach An improvement over LEACH (E-LEACH) [6]Protocol, E-Leach Protocol, Load Balancing, [19] [20] suggests selection of cluster head by theirCluster Based Routing, Omnet++. remaining energy when the energy level of nodes drops below 50% of the initial energy. Node1. Introduction having maximum energy is selected as cluster head. However clustering schemes do notSensor nodes [1] [2] are energy constrained guarantee exactly equal number of nodes as clusterbecause they carry a limited energy. Because head during different rounds and clusters do notnodes are deployed randomly in a harsh have equal number of nodes. Due to this toothed 196 All Rights Reserved © 2012 IJARCET
    • ISSN: 2278 – 1323 International Journal of Advanced Research in Computer Engineering & Technology Volume 1, Issue 5, July 2012cluster formation, nodes of smaller cluster have Here P is the desired percentage to become asmaller TDMA schedule than the others. So these cluster head; r, the current round; and G, thenodes send more data frames to their respective set of nodes that have not being selected as acluster head over a round. As a result, cluster head cluster head in the last 1/P rounds. After theof that cluster has to send more aggregated data to cluster-heads are selected, the cluster-headsthe base station. So all nodes of a smaller cluster advertise to all sensor nodes in the networktransmit larger number of data, causing contains that they are the new cluster-heads.deplete their energy faster as compared to others. Once the sensor nodes receive theThis makes overall consumption of network advertisement, they determine the cluster thatuneven. they want to belong based on the signalThe rest of this paper is prepared as follows strength of the advertisement from the clustersegment 2 briefly describes the literature of heads. The sensor nodes inform theclustering for the WSN in different areas, Segment appropriate cluster head that they will be a3 describes the detailed study of the related member of that cluster. Afterwards, the clusterresearch. And the proposed algorithm is discussed. head assigns the time on which the sensorSegment 4 discusses the simulation and its results nodes can send data to the cluster-heads basedand lastly concludes the paper. on a TDMA approach.2. Literature of Clustering For WSNCommunication of data is the most energyconsuming process of nodes. Clustering of nodesin a cluster is an energy efficient approach [20] byavoiding the long distance communication ofnodes. In static clustering scheme, clusters arefixed and one node acts as a cluster head for eachcluster. Cluster head is responsible for gatheringdata of nodes in the respective cluster and forsending the data o base station located at fardistance. A cluster head node is consuming moreenergy than other nodes and hence is more proneto energy failure. Cluster head node failure resultsin loss of data of that cluster. Figure.1: LEACH Protocol with Cluster Head and Cluster Nodes 2.1 LEACH During the steady phase, the sensor nodes LEACH scheme does the selection of cluster transmit data to their respective cluster head. head randomly among the nodes during each Each node sends data to respective cluster round. Operation of LEACH [6] [19] is head during its time slot and minimizes the carried out in two phases during a round: set- consumption of energy by entering into sleep up phase and steady phase. During the set-up mode for remaining time period. Cluster head phase, a sensor node chooses a random aggregates data and sends to the base station. number between 0 and 1. If this random After a certain period of time spent on the number is less than the threshold T (n), the steady phase, re-clustering is done. sensor the sensor node is a cluster-head. T ESCAL [7] uses LEACH as its base but the (n) is calculated as in equation (1) cluster heads do not send the aggregated data directly to the base station. A Cluster head send the data to nearby cluster head that is close to the base station and conserve the energy by not sending the data to a long distance. 197 All Rights Reserved © 2012 IJARCET
    • ISSN: 2278 – 1323 International Journal of Advanced Research in Computer Engineering & Technology Volume 1, Issue 5, July 20122.2 Energy-LEACH 3. Conception of Improved ClusterOne of the disadvantages of the LEACH is Algorithm For Load Balancingthat the cluster head rotation does not take intoaccount the remaining energy of sensor nodes. Wireless sensor networks represent the nextA node may not have sufficient energy to generation of sensing machines and structures.carry out the whole round and can be selected Inherent limited energy resource is the one of theas a cluster head. E-LEACH [6] [19] [20] limitations of wireless sensor nodes. In order toapplies both LEACH and new approach for distribute the energy dissipated throughout thecluster head selection. When the remaining wireless sensor network, data load of the sensorenergy is larger than 50% of the initial energy nodes must be balanced. Clustering is one of theof a node, the LEACH algorithm is applied as key mechanisms for load balancing. Clusteringin equation (1). Otherwise a new approach algorithms [20] may result in some clusters thatwhich considers the remaining energy in each have more members than other clusters in thenode is applied as in equation (2). network and uneven cluster sizes negatively affect the load balancing in the network. In our proposed work we improve a cluster algorithm for load balancing in clusters. Efficiency of WSNs measured by the total distance between nodes to the base station and data amount that has is transfer. Cluster–Head which is totally responsible for the creating cluster and cluster nodes may affect the performance of the cluster. The purposed algorithm we choose a Master Node and viceHere P is probability to become a cluster head, master node for regions and sub regions. To findEredidual is remaining energy of node and out the master node we partition the region andEinit is initial energy of a node. If value of find out the centered of region, by which we selectT(n) is larger than a number between 0 and 1 it the master node. For every partitioned region againbecomes a cluster head. portioned if required and much like depend onAfter selection of cluster head, cluster master node and nodes in that partitioned area. Ourformation is done. A cost is calculated by each purposed algorithm we can find the better lifetimenode to join a cluster, which includes the and energy efficiency.remaining energy and signal power strength ofCluster head. A node joins the cluster head oflargest cost value. Cost (i) = CH (i) remaining energy + CH (i) signal strengthHere CH (i) remaining energy and CH (i) signalstrength are remaining energy and signalstrength of Cluster Head (i). Nodes calculatethe cost value and join the cluster head with Figure.2: Random Formation of Nodes in Networkmaximum cost value by sending the joinmessage to cluster head.Each cluster head decides a TDMA timeschedule and informs the member nodes aboutthe schedule. The nodes then transmit thesensed data to the cluster head during itstimeslot. A sensor node sends data to clusterhead only when a certain condition is satisfiedsuch as “Does the temperature exceed 30degree?” If condition is not satisfied, nodes goto sleep mode to reduce energy consumption. 198 All Rights Reserved © 2012 IJARCET
    • ISSN: 2278 – 1323 International Journal of Advanced Research in Computer Engineering & Technology Volume 1, Issue 5, July 2012Figure.3: Division of region and selection of Master and 4. This master node broadcast a message to Vice Master Node of Cluster (top layer) the all node of that region and receives reply message [a] from the node. 5. If the location or distance and no of node is more than the efficiency [b] of master node then partitioned the region into four equal sub regions and go to step 6. Else Go to step 7. 6. Find the centre of region and repeat stepFigure.4: Division of sub region and selection of Master 2. and Vice Master Node of Cluster (middle layer)Figure.5: Division of sub region and selection of Master and Vice Master Node of Cluster (bottom layer)Figure 2 shows the random deployment of nodes ina network; Figure 3, Figure 4 and Figure 5 showshow cluster are formed with master node and vicemaster node by region division. Region divisionhelps us to make cluster balanced.When the master node will be dead the vice masternode act as a master node. After finishing the setupphase the steady state phase will start and nodestransmit data. When all the nodes within thecluster finish sending data the master nodesperforms some computation on it and sends it tobase station using multi-hop communication. PROPOSED ALGORITHM:Setup Phase: Figure.6: Hierarchical Structure of Cluster in proposed Work 1. First randomly generated the nodes and Measure the region and find the centre of 7. The node id is stored in the master node region. and , (The master node sends a message 2. Find nodes as close as centre is called set about the information of all neighbor of master node, store the set and specify a nodes of that region to the node, master node from the set on the basis of Or energy level of the node. Node sends a hello signal to the neighbor nodes). Update the neighbors table. 3. ID of master node is stored in to the table of previous master node and vice versa. 199 All Rights Reserved © 2012 IJARCET
    • ISSN: 2278 – 1323 International Journal of Advanced Research in Computer Engineering & Technology Volume 1, Issue 5, July 2012Steady State Phase: 4.2 Simulation Result 8. Node to master node communication: Death Rate is the measurement of number of Nodes sensing and transmitting data to the node dead in the field with time. A node death immediate master node in their allotted can be some physical damage or a node might time slot. The master node collects data be out of energy. A network is reliable if the and processes the data. After that the node death rate is low. A reliable network will master node transmission is start. All have a better data gathering rate i.e. units master nodes do the same task. received at base station will also be high. The Results of the simulation are shown in theWhen the data reach to base station the steady Table 2, which shows the Analysis of the deadstate is repeated, nodes with varying network load and Table 3, which shows the Analysis of the remaining a. Reply message contains the energy level. energy consumption by various algorithm. b. Efficiency of master node is measured by No. of Dead Nodes the master node energy level, signal Time Proposed E- receiving time and delay of access. LEACH Algorithm LEACH4. Implementation and Simulation 10 2 4 7 15 4 7 12This section describes the simulation results 20 5 9 17obtained during the investigation phases of thesimulation. We used OMNeT++, is an object- 25 7 11 19oriented modular discrete event network simulator 30 7 11 22[16] to implement our improved cluster algorithmfor load balancing in WSN. 35 8 13 27 40 10 15 31 4.1 Simulation Parameters 45 12 17 34 The parameter used in simulating and Table.2: Analysis of Dead Nodes Comparison implementation of the simulation for improved cluster algorithm for load Remained Energy balancing is given in table 1 below. Time Proposed E- LEACH Simulation Values Algorithm LEACH parameters 10 298 284 249 Simulation time 1200 sec 15 295 270 225 Number of nodes 100 Channel type Channel/wireless 20 289 258 202 channel 25 280 236 186 Node distribution Randomly distributed 30 275 221 172 Network topology Loss topology 35 271 209 159 (900x900 m2) 40 263 193 143 Number of trials 10 times Initial node power 2 joule 45 257 182 137 Simulator Omnet++ 50 249 178 132 Table.3: Analysis of Remaining Energy Consumption Table.1: Summery Of the Parameters Used In the Comparison Simulation Experiments. 200 All Rights Reserved © 2012 IJARCET
    • ISSN: 2278 – 1323 International Journal of Advanced Research in Computer Engineering & Technology Volume 1, Issue 5, July 2012 5. Conclusion and Future Work The overall conclusion is that improved cluster algorithm for load balancing is best choice to move towards a network with less energy consumption as it involves energy minimizing techniques like multi-hop, clustering and data aggregation. From the simulation results, we can draw a number of conclusions. Firstly the, number of dead node is less than the previous technologies. Then secondly, if number of dead node occurs by the new version are less that means the network energy remaining using improved cluster algorithm for load balancing is more than the remaining network energy using the previous techniques. We prove that in figure 8, which means the improved versionFigure.7: Dead node comparison in network of cluster algorithm for load balancing, outperforms the previous version of clustering algorithms. However there are many more issues, which are to be considered related to minimizing the power usage and the network life time in this. We can still minimize the energy consumption and extend the network life time by improving the clustering technique. 6. References [1] O. Younis, M. Krunz and S. Ramasubramanian, “Node Clustering in Wireless Sensor Networks: Recent Development and Deployment Challenges,” IEEE Networks, May/June-2006, pp.20-25. [2] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, E. Cayirci, “Wireless Sensor Networks: a survey,” Figure.8: Remaining Energy Consumption Elsevier Science Journal of Computer Networks, Comparison in Network vol. 38, 2002, pp. 393-422. [3] Abbasi, M. Younis, “A survey on clustering algorithms for wireless sensor networks,” vol. 30,Figure 7, shows the simulation graphs for 2007, pp. 2826-2841.analysis of number of dead nodes occur in [4] B. Deosarkar, N. Yadav and R. P. Yadav,different algorithms and Figure 8 shows the “Clusterhead Selection in Clustering Algorithmssimulation graph for consumed energy for for Wireless Sensor Networks; A Survey,” In Proc.the nodes in different algorithms Int. Conf. Computing, Communication and Networking (ICCCN 2008), Dec 18-20, 2008,respectively. Our goals in conducting the Karur, Tamilnadu, India.simulation are as follows: Compare the [5] W, Heinzelman, A.Chandrakasan andperformance of the different algorithms Vs. H.Balakrishnan, “Energy- EfficientLifetime of a node (dead nodes), No. of Communication Protocol for Wireless Microsensordifferent clusters algorithms Vs. Energy Networks”, In Proc.33rd HICS, Jan. 4-7, 2000, Vol.2, pp. 1-10.consumption. [6] Ki Young Jang, Kyung Tae Kim, Hee Young Youn, “An Energy Efficient Routing Schemes for 201 All Rights Reserved © 2012 IJARCET
    • ISSN: 2278 – 1323 International Journal of Advanced Research in Computer Engineering & Technology Volume 1, Issue 5, July 2012Wireless sensor Networks,” In Proc. 5th ICCSA, [18] K. Subbu and X. Li, “SFRP: A selective2007, pp. 399-404. flooding-based routing protocol for clustered[7] C. Jing, T. GU and L. Chang, “ESCAL: An wireless sensor networks”, IEEE Radio andEnergy-Saving Clustering Algorithm Based on Wireless Symposium. RWS‟ 10.LEACH,” Proc. IEEE Int. Symposium on [19] H. Lu, J. Li, and G. Wang, “A novel energyKnowledge Acquisition and Modeling Workshop, efficient routing algorithm for hierarchically2008. KAM Workshop 2008, pp. 403-406. clustered wireless sensor networks”, International[8] F. Ye, A. Chen, S. Liu, L. Zhang, “A scalable Conference on Frontier of Computer Science andsolution to minimum cost forwarding in large Technology, 2009, pp. 565-570.sensor networks,” Proceedings of the tenth [20] S.K. Singh, M.P. Singh, and D.K. Singh, “AInternational Conference on Computer survey of Energy-Efficient HierarchicalCommunications and Networks (ICCCN), pp. 304- Clusterbased Routing in Wireless Sensor309, 2001. Networks”, International Journal of Advanced[9] Akkaya K. and Younis M., 2005"A survey on Networking and Application (IJANA), Sept.–Oct.routing protocols for wireless Sensor network," 2010, vol. 02, issue 02, pp. 570–580.journal of Adhoc Networks, vol 3, 325-349 .[10] Heinzelman W.R., Chandrakasan A, andBalakrishnan H., 2000"Energy EfficientCommunication Protocol for Wireless Microsensor Networks," Proc. 33rd Hawaii Int’l. Conf.Sys. Sci. [11] Lin SHEN and Xiangquan SHI: A LocationBased Clustering Algorithm for Wireless SensorNetworks, INTERNATIONAL JOURNAL OFINTELLIGENT CONTROL AND SYSTEMS,VOL. 13, NO. 3, SEPTEMBER 2008, 208-213 [12] M. Bani Yassein, A. Al-zou’bi,Y.Khamayesh,W. Mardini: “Improvementon LEACH Protocol of Wireless SensorNetwork(VLEACH).” [13] Mudasser Iqbal , Iqbal Gondal, LaurenceDooley: “An Energy-Aware Dynamic ClusteringAlgorithm for Load Balancing in Wireless SensorNetworks” 2006..[14] J.-H. Chang and L. Tassiulas, “MaximumLifetime Routing in Wireless Sensor Networks,”Proc. Advanced Telecommunications andInformation Distribution Research Program(ATIRP2000), College Park, MD, pp 334-335,Mar. 2000.[15] C. Rahul, J. Rabaey, “Energy Aware Routingfor Low Energy Ad Hoc Sensor Networks,” IEEEWireless Communications and NetworkingConference (WCNC), vol.1, Orlando, FL, pp. 350-355, March 17-21, 2002.[16] OMNET ++ Website, www.omnetpp.org.[17] Jun Wang, Yong-Tao Cao, Jun-Yuan Xie,Shi-Fu Chen: “Energy Eficient BackoffHierarchical Clustering Algorithms for Multi-HopWireless Sensor Networks”, JOURNAL OFCOMPUTER SCIENCE AND TECHNOLOGY2011. 202 All Rights Reserved © 2012 IJARCET