Corona based energy efficient clustering in wsn 2


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Corona based energy efficient clustering in wsn 2

  1. 1. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 3, April (2013), © IAEME233CORONA BASED ENERGY EFFICIENT CLUSTERING IN WSNSyed Abdul Sattar1, Mohamed Mubarak.T2, Vidya PV3, Appa Rao41Royal Institute of Technology and Science, Dean,Department of Computer ScienceHyderabad,Andra Predesh State,India2Royal College of Engineering, Asst Professor,Department of Computer ScienceTrichur,Kerala state,India3Royal College of Engineering, B.Tech Student, Department of Computer ScienceTrichur,Kerala state,India4GITAM Institute of Technology,GITAM University ,Professor and Head,Department ofComputer Science, Visakhapatnam,Andra Predesh State ,IndiaABSTRACTWireless sensor network represents one of the most interesting research areas with profoundimpact on technological development. Here we implement an energy efficient approach for optimalcluster head selection and clustering. We also pinpoint cluster head rotation technique using theconcept of back off timer that prolongs the life time of the network. Addition and deletion of nodescan be done in the clustered network without affecting the existing infrastructure.Index Terms - Wireless Sensor Networks, Corona, Clustering, Cluster Head, Routing, Nodes, Sink,Back off Timer, VCCB, Optimal Distance.I. INTRODUCTIONMany future applications will increasingly depend on embedded wireless sensor networks. Asensor network consists of numerous sensor/actuator devices. Wireless Sensor Networks haveemerged as an important new area in wireless technology. In the near future, the wireless sensornetworks are expected to consist of thousands of inexpensive nodes, each having sensing capabilitywith limited computational and communication power, which enable us to deploy a large-scale sensornetwork. A critical aspect of applications in wireless sensor network is network lifetime.Wireless sensor network are usable as long as they can communicate sensed data to processednode. Sensing and communication are important activities and they consume energy. So powermanagement and sensor scheduling can effectively increase the networks lifetime. The use of wirelesssensor networks is increasing day by day and at the same time it faces the problem of energyconstraints in terms of limited battery lifetime.INTERNATIONAL JOURNAL OF ADVANCED RESEARCH INENGINEERING AND TECHNOLOGY (IJARET)ISSN 0976 - 6480 (Print)ISSN 0976 - 6499 (Online)Volume 4, Issue 3, April 2013, pp. 233-242© IAEME: Impact Factor (2013): 5.8376 (Calculated by GISI)www.jifactor.comIJARET© I A E M E
  2. 2. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 3, April (2013), © IAEME234WSN has considerable technical challenges in data processing and communication to dealwith dynamically changing Energy, Bandwidth and Processing power. Another important issue inWireless Sensor Network is to maximize Sensor Network lifetime. The vital issue in WSN is tomaximize the network operational life. In order to achieve this, it is necessary to minimize the energyutilization of a node. Most of the energy consumption in wireless sensor node is attributed totransmitting/receiving, processing, and forwarding the data to neighboring nodes.Clustering has been shown to improve network lifetime, a primary metric for evaluating theperformance of a sensor network. The clustering techniques proposed for data processing typicallyconsider many parameters, such as the distance between the nodes, and assume that nodes are morereliable.The sensors are capable of sensing the data from the environment in which they are deployed,processes that data and transmit it to the base-station (BS). The sensor circuit senses the environmentand converts the signals into electrical signals which are then transmitted to the BS using a transmittervia a routing node. In clustering, nodes with higher power levels perform the fusion of data gatheredfrom the other sensor nodes and transmit the aggregated data to the base-station (BS) while the nodeswith low power levels only perform the sensing of the environment. They transmit the sensed data tothe higher node, known as the cluster-heads (CHs) which are at a lesser distance to the base station.The cluster formation and the assignment of special tasks to the cluster heads (CHs) reduce the powerdissipation within a particular cluster, which improves the scalability of the sensor network. Also byaggregating the sensed data, the amount of data to be transmitted to the base-station (BS) is reducedand the lifetime of the overall sensor network is increased.II. RELATED WORKSPaper [1] proposes a model for energy efficient clustering and cluster head selection method.It is based on a circular monitoring area with a uniform node density and a sink node at the center.The area is divided into concentric circles known as corona, each of width R/2, where R is thetransmission range of the sensor node. Cluster head selection is performed by finding out the optimaldistance from VCCB, where VCCB lies at the midway between two concentric circles.One of the main design goals of WSNs is to carry out data communication while trying toprolong the lifetime of the network and prevent connectivity degradation by employing aggressiveenergy management techniques [2].The clustering concept offers tremendous benefits for wireless sensor networks. Howeverwhen designing for a particular application, designers must carefully examine the formation ofclusters in the network. Depending on the application, certain requirements for the number of nodes ina cluster or its physical size may play an important role in its operation. This prerequisite may have animpact on how cluster heads are selected in this application [3].There are many clustering protocols are exists, such as LEACH, HEED etc. As the need forefficient use of WSNs on large regions increased in the last decade dramatically, more specificclustering protocols were developed to meet the additional requirements (increased network lifetime,reduced and evenly distributed energy consumption, scalability, etc.). The most significant and widelyused representatives of these focused on WSN clustering protocols (LEACH, EEHC, and HEED).Some of them (such as LEACH, EEHC, and their extensions) follow a random approach for CHelection (the initially assigned probabilities serve as the basis for the random election of the CHs),whereas others (like HEED and similar approaches) follow a hybrid probabilistic methodology(secondary criteria are also considered during CH election—i.e., the residual energy) [4].The LEACH protocol [3] is an application-specific clustering protocol, which has been shownto significantly improve the network lifetime. It assumes that every node is reachable in a single hopand that load distribution is uniform among all nodes. LEACH assigns a fixed probability to everynode so as to elect itself as a CH. The clustering process involves only one iteration, after which anode decides whether to become a CH or not. Nodes take turns in carrying the role of a CH [5].
  3. 3. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 3, April (2013), © IAEME235HEED (Hybrid Energy-Efficient Distributed clustering), has four primary goals: (i)prolonging network lifetime by distributing energy consumption, (ii) terminating the clusteringprocess within a constant number of iterations/steps, (iii) minimizing control overhead (to be linear inthe number of nodes), and (iv) producing well-distributed cluster heads and compact clusters. Inclassical distributed systems, a node can either be a server or a source, but not both. A fixed numberof servers are known to every source in the system, and a server is always available for processing. Inour model, every node can act as both a source and a server (cluster head), which motivates the needfor efficient algorithms to select servers according to the outlined system goals [6].The execution of a clustering algorithm can be carried out at a centralized authority (e.g., abase station) or in a distributed way at local nodes. Centralized approaches require global informationabout the network topology. Banerjee et al. [7] proposed a centralized technique that does not requireknowledge of node locations. Even though t is a spanning tree based idea, we are designing a newidea which is also a network in which node locations are unknown [4].III. SYSTEM MODELA. NEED FOR CLUSTERINGWSN offer unique systems for creating communications infrastructures on-demand. Their useis dependent on the effective deployment of these systems to areas of interest. There are severalchallenging issues involved in the deployment of WSN, mostly due to their small size and largenumber of nodes required to establish proper operation.WSN is an emerging technology that shows great promise for various futuristic applicationsboth for mass public and military. The sensing technology combined with processing power andwireless communication makes it lucrative for being exploited in abundance in future. The inclusionof wireless communication technology also incurs various types of security threats. A WSN must alsobe self-monitoring and able to proactively reconfigure to mitigate certain malfunctions before theyactually occur.Clustering means grouping of nodes. As each node depends on energy for its activities, thishas become a major issue in wireless sensor networks. The failure of one node can interrupt the entiresystem or application. Every sensing node can be in active (for receiving and transmission activities),idle and sleep modes. In active mode nodes consume energy when receiving or transmitting data. Inidle mode, the nodes consume almost the same amount of energy as in active mode, while in sleepmode, the nodes shutdown the radio to save the energy.B.CLUSTERING BASICSIn cluster based architectures, mobile nodes are divided into virtual groups. Each cluster hasadjacencies with other clusters. All the clusters have the same rules. A cluster can be made up of aCluster Head node and Cluster Members. In this kind of network, Cluster Head nodes are used tocontrol the cluster and the size of the cluster is usually about one or two hops from the Cluster Headnode. Grouping sensor nodes into clusters has been widely adopted by the research community tosatisfy the above scalability objective and generally achieve high energy efficiency and prolongnetwork lifetime in large-scale WSN environments. The corresponding hierarchical routing and datagathering protocols imply cluster-based organization of the sensor nodes in order that data fusion andaggregation are possible, thus leading to significant energy savings.
  4. 4. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 3, April (2013), © IAEME236Fig 1 Clustered NetworkThe sink node gets all information from the cluster heads those are connected to the othernodes under control of them. Here is the most challenging part will come to place that, if theclustering head pass the same events to the sink node it will leads to more energy consumption.Another fact is that if the clustering node having the capability to compress/data aggregation energyconsumption can be reduced to a optimum level. So, here we select the clusters as the nodes whichhaving maximum resources and monitoring power.IV. PROPOSED MODELThis paper mainly focuses on energy efficient and a secure Wireless Sensor Network. We useclustering method for communication between nodes and sink, since it is energy efficient whencompared to single hop and multi hop routing.All non-CH nodes transmit their data to the CH they are connected to, while the CH nodereceives data from all the cluster members, performs specific processing functions on the data (e.g.,aggregation, filtering, compression, etc.), and forwards data to the BS. We implement a clusteringmechanism which performs optimum selection of cluster heads and rotates the role of cluster head inan energy efficient way.A. ASSUMPTIONSThe proposed model made some assumptions. These are• The nodes are deployed over circular monitoring area A of radius Z with uniform nodedistribution density ρ.• The sink node will be plotted at the centre.• The nodes are deployed randomly on the region.• All nodes having same energy.• Selection of CHs based on timer expiration.B.STEPS NEEDEDThe various steps that we follow are:Step 1: Read the maximum number of nodes that must be deployed, the sensing range andtransmission range of the node, the radius of the circular area, and the coordinates of the centre of thecircular area where the sink node is to be plotted.Step 2: We randomly choose a set of coordinates that come within the circular region and plotthem in the specified area. For this, we compare the distance between the chosen coordinate and thecentre, and the radius of the circular area. We plot the point only if the distance falls under the givenradius. We count the number of points plotted.
  5. 5. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 3, April (2013), © IAEME237Step 3: Now we divide the circular area into a number of concentric circles each of width R/2,where R is the maximum transmission range of the node. Each of these concentric circles is calledcorona. We find the Euclidian distance of each node from the sink node and then the sensor nodes areassigned concentric circle index using the formulaFig 2: Corona based WSN modelStep 4: In order to implement energy balanced clustering, the concept of Virtual Concentric CircleBand (VCCB) is introduced, where each sensor node calculates their respective VCCB index usingthe formulaFig 3: Assigning VCCB to nodesThe value of δ depends on node density; If the sensing area is densely populated, the value of δ issmall, for sparsely populated area, the value of δ is large. If the distance of a node from the sink, dsi,
  6. 6. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 3, April (2013), © IAEME238falls within VCCB index, then the corresponding sensor node is chosen as a probable candidate forcluster head election. These candidate nodes then calculate their distance from the centre of theirrespective VCCB asHere we use the concept of a back-off timer. Its initial value is proportional to the distance of thecandidate from the centre of VCCB. For a node Ni, the initial value of back off timer is given byStep 5: The cluster formation phase begins when the sink node sends START message to thecandidates. Upon receiving this start message, each candidate starts its back of timer. Since the backoff timer value is proportional to the distance of the candidate from the centre of VCCB, the back offtimer of the node near to the centre will expire first. The node, whose back of timer expired first, willsend as advertisement to all nodes within the radio range R/4, announcing itself as the cluster head.All the cluster head candidates within this radio range, will stop their back off timer and all the clusterhead candidates as well as non-cluster head candidates within this range will acknowledge the receiptof announcement, thus forming a cluster. This process is carried out throughout the network area, thusforming a number of non uniform clusters.Step 6: In order to prolong the life time of the network, we change the role of cluster head with ina cluster when the remaining energy of the current head lowers below a particular threshold value.Find out the candidate nodes among the members of that cluster. Sink node sends a START messageto those candidates, upon which each candidate starts their back off timer. The nodes whose timerexpires first will be chosen as the new cluster head.C. IMPLEMENTATION OF SCALABILITYMany applications of wireless sensor networks adopt hierarchical structure for the scalability andsimplify of management. Clustering is the most popular method that imposes such a scalabletopology. Here we implement addition and deletion of nods to the existing sensor network.In order to add a new node in to the specified clustered network, we keep track of an array insidethe node structure for every cluster head which stores the ids of the member nodes of thecorresponding cluster heads. Then new node sends a message to sink node about its arrival then it willforwarded to all cluster heads. After that it will join to the cluster head that has minimum distancefrom that node and it should have high monitoring capability.Deletion means removing out-of-date, redundant, or inconsistent nodes. Then update the nodes inclusters to eliminate redundancy. In order to perform deletion we can use the same array that definedfor the addition of nodes. Delete the node id from the array for deletion and update the array. Thegoals of this scalability approaches are maintaining stable clustering structure, minimizing theoverhead for the clustering set up, maximizing lifespan, and achieving good end to end performance.V. SIMULATION RESULTSThe network simulation is done in MATLAB environment. A circular area with specifiedradius is considered. The nodes have to be deployed independently and randomly. Certain numbers ofnodes are deployed over the area. The nodes which satisfy the criteria specified in the algorithm willplot over the area. That is, we compare the distance between the chosen coordinate and the centre, andthe radius of the circular area. We plot the nodes only if the distance falls under the given radius.
  7. 7. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 3, April (2013), © IAEME239The probable candidates and the cluster members are represented with various colors in thegraph. The transmission energy of the nodes while sending k bits of data over the distance will foundout by the equations:Where is the transmission electronics energy and d0 is the optimum distance.The energy consumption of sensor node to receiver k bits of data is given by:The messages exchanged between each and every node is represented by colored lines in thegraph. Probable candidates are those nodes which are more suitable nodes to become cluster heads.These nodes are selected on the basis of calculated VCCB indices during the execution.Cluster heads are selected by timer expiration. The candidate node whose back off timerexpires first will be chosen as the cluster heads. After the selection of cluster heads they advertisesthese information to the nodes within the R/4 transmission range of the selected cluster head.0 100 200 300 400 500 600 700 800 900 100001002003004005006007008009001000Fig 4 Clustered NetworkHere energy is the heterogeneity parameter. Whenever the remaining energy less than aparticular threshold, cluster head rotation will be performed. Cluster head rotation is performed byfinding next powerful probable candidate which has higher monitoring capability. So, the sink nodesends START message to these candidates and they start their back off timer. As in the previous casethe node whose timer expires first, it will become the cluster head.This kind of cluster head rotation avoids the need for reclustering. Reclustering takes moreenergy to maintain the topology and all the nodes will again performs clustering and joins to theclusters. In our approach, we can avoid reclustering thus avoids the higher energy utilization. Henceenergy consumption of corona approach is less than that of other clustering approaches.Scalability is one of the major issues when WSN is considered. An efficient sensor networkshould be extensible without affecting the performance characteristics. Here we implement additionand deletion of nodes from the sensor network.
  8. 8. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 3, April (2013), © IAEME240For performing addition to the wireless sensor network, create an array that stores the IDs ofthe member nodes for each cluster head. Also create a variable that stores the number of members.When a new node wants to join to the sensor network, new node sends the information to the sinknode about its arrival. Then find the distance to each cluster head and join to the cluster head whichhas minimum distance from the new node. After join to the cluster head member array of that clusterhead will be update by adding the new node ID.Deletion means removing the redundant or lower energy nodes from the sensor network.Deletion of such nodes improves the performance of the network because, these nodes can’tmonitoring the area efficiently and sending messages to these kinds of nodes will leads to unnecessaryenergy consumption. Here deletion is done based on the residual energy. Whenever energy of theexisting node reduces than the threshold value, the IDs of such nodes are maintained in an array.Already we have count of the members under each cluster head. We check the ID of the node to bedeleted with the member IDs. Then delete the ID of the node to be removed from its CH’s memberarray. Update the array after deletion.COMPARISON WITH LEACHLEACH is called “Energy efficient Adaptive protocol for clustered Wireless sensornetworks”. Low Energy Adaptive Clustering Hierarchy (LEACH) is the first energy efficient routingprotocol for hierarchical clustering. LEACH is a self organized protocol based on a probabilityapproach. LEACH mainly focuses homogeneous environments. The probability to become a CH afteronce it is selected is higher because in LEACH all nodes get chance to become CH and it leads toreduced lifetime. In our protocol, we select only certain number of efficient candidates to become CHand it leads to enhanced lifetime of cluster. LEACH sends JOIN request to all other nodes overdeployed area leads to higher energy consumption. In corona-based approach we send JOIN messageonly to those nodes that are within the radio range which leads low energy consumption.The following figure shows the comparison between LEACH and corona based approachbased on the number of nodes deployed and number of probable candidates to become CH.100 150 200 250 300 350 400 450 50050100150200250300350400450500NoofProbableCandidatesforCHNo of Nodes DeployedLEACHCorona-based AlgorithmFig 5 Number of Nodes Deployed vs. Number of Probable Candidates for CH GraphFrom the analysis of above graph, it is clear that, in corona based approach we select onlyoptimum number of cluster heads.
  9. 9. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 3, April (2013), © IAEME241The following table describes the various statistics of the corona based approach:Number ofnodes deployedNumber ofprobablecandidatesNumber ofCHs selectedduring round 1Number ofnodes failed afterround 1Number ofCHs selectedduring round 2100 64 26 0 0200 128 34 21 21300 190 34 27 27400 251 39 33 33500 331 40 36 36600 378 40 36 36Table 1 Simulation Analysis-1During each round of CH rotation, the number of CHs selected equals the number of CHsfailed during the previous round. This ensures a clustering method that effectively monitors all thenodes in the network even after a certain number of rounds.100 150 200 250 300 350 400 450 500 550 6002628303234363840NoofCHs(Round1)No of Nodes DeployedCorona-based AlgorithmFig 6 Number of Nodes Deployed vs. Number of CHs Selected (During Round 1)After the first round of CH selection, a certain number of CHs fail as their energy fall below aparticular threshold value. Those nodes are deleted and the same numbers of CHs are selected in thesecond round of CH rotation.100 150 200 250 300 350 400 450 500 550 6000510152025303540NoofCHs(Round2)No of Nodes DeployedCorona-based AlgorithmFig 7 Number of Nodes Deployed vs. Number of CHs Selected (During Round 2)
  10. 10. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 3, April (2013), © IAEME242The time elapsed for first round of cluster head selection and second round of cluster head rotationfor various numbers of nodes deployed can be tabulated as follows:Number of nodes deployedTime taken for first roundof CH selection(in seconds)Time taken for secondround of Ch rotation(in seconds)100 329.631565 0.756115200 446.454966 190.816695300 681.083411 266.269403400 692.684151 264.298860500 863.258635 319.014914600 1024.648643 387.028500Table 2 Simulation Analysis-2VI. CONCLUSIONSNode clustering is a useful topology-management approach to reduce the communicationoverhead and exploit data aggregation in sensor networks. Clustering is highly efficient because thenodes are deployed over a large area which is also insecure. So, monitoring is one of the critical tasksover a large area. In our corona based approach the best monitoring can be assured because eventhough one CH is drained, we have a possibility to rotate them and the monitoring is more specificdue to different corona exist over a region. The major concern of scalability can also be resolved bydynamic addition and deletion of nodes in the network, maintaining the same performance efficiencythereby aiding a wide range of applications.REFERENCES[1] Location Based Clustering in Wireless Sensor Networks by Ashok Kumar, Narottam Chand andVinod Kumar published in World Academy of Science, Engineering and Technology 60 2011[2] Routing techniques in wireless sensor networks: a surveyjamal n. Al-karaki, the Hashemiteuniversity Ahmed e. Kamal, Iowa state university IEEE wireless communications • December 2004.[3] A Survey of Clustering Algorithms for Wireless Sensor Networks D. J. Dechene, A. El Jardali,M. Luccini, and A. Sauer.[4] Clustering in Wireless Sensor Networks Basilis Mamalis, Damianos Gavalas, CharalamposKonstantopoulos, and Grammati Pantziou , Zhang/RFID and Sensor Networks AU7777_C012 PageProof Page 323 2009-6-24[5] Node Clustering in Wireless Sensor Networks: Recent Developments and Deployment Challenges, Ossama Younis, Marwan Krunz , and Srinivasan Ramasubramanian, University of Arizona , 0890-8044/06/$20.00 © 2006 IEEE , IEEE Network • May/June 2006.[6] Distributed Clustering in Ad-hoc Sensor Networks: A Hybrid, Energy-Efficient Approach byOssama Younis and Sonia Fahmy, Department of Computer Sciences, Purdue University, 250 N.University Street, West Lafayette, IN 47907–2066, USA.[7] S. Banerjee and S. Khuller, “A Clustering Scheme for Hierarchical Control in Multihop WirelessNetworks,” Proc. IEEE INFOCOM, Apr. 2001, pp. 1028–37.[8] L.Malathi and Dr.R.K.Gnanamurthy, “A Novel Cluster Based Routing Protocol With LifetimeMaximizing Clustering Algorithm”, International Journal of Computer Engineering & Technology(IJCET), Volume 3, Issue 2, 2012, pp. 256 - 264, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375.[9] Meghana. N.Ingole, M.S.Bewoor and Mr.S.H.Patil, “Context Sensitive Text SummarizationUsing Hierarchical Clustering Algorithm”, International Journal of Computer Engineering &Technology (IJCET), Volume 3, Issue 1, 2012, pp. 322 - 329, ISSN Print: 0976 – 6367, ISSN Online:0976 – 6375