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Dc31712719

  1. 1. Priya, Satyesh Sharan Singh, Mukesh Kumar, Rohini Saxena / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.712-719 Energy And Time Delay Efficient Wireless Sensor Network By Least Spanning Tree Algorithm: A Survey Priya1, Satyesh Sharan Singh2, Mukesh Kumar3, Rohini Saxena4, 1 PG Student ECE, SHIATS(Deemed-to-be-university), U.P., India, 2 PG Student ECE, SHIATS (Deemed-to-be-university), U.P., India, 3 Assistant professor, ECE, SHIATS (Deemed-to-be-university), U.P., India, 4 Assistant professor, ECE, SHIATS (Deemed-to-be-university), U.P., India,Abstract In this paper we are going to survey the use the available bandwidth and energy efficiently.different type of topology and techniques for Energy usage is an important issue in the design ofmaking an energy efficient WSN with least time WSNs which typically depends on portable energydelay approach .WSNs are used in defense field sources like batteries for power .WSNs is large scalewhere lest time delay and life of sensors are most networks of small embedded devices, each withimportant because the life of solider are depends sensing, computation and communicationon fast information transmission . Hence energy capabilities. They have been widely discussed inand time delay are very scarce resources for such recent years. Coverage is one of the most importantsensor systems and has to be managed wisely in challenges in the area of sensor networks. Since theorder to extend the life of the sensors and energy of sensors are limited, it is vital to cover theminimizing time delay for the duration of a area with fewer sensors. Generally, coverage inparticular mission. In past a lot of cluster based sensor networks is divided into area coverage, pointalgorithm and techniques were used. In this coverage, and boundary coverage subareas.paper we also find out all type of algorithm, Coverage does not ensure connectivity of nodes.. Intheir application and limitation and present WSNs the sensortechniques to overcome the problems of low nodes are often grouped into individual disjoint setsenergy and time delay of sensor and compare called a cluster, clustering is used in WSNs, as itthem with least spanning tree based algorithms provides network scalability, resource sharing andand techniques . efficient use of constrained resources that gives network topology stability and energy savingKeywords: Wireless sensor networks, energy attributes. Clustering schemes offer reducedefficient clustering, LEACH, energy efficient communication overheads, and efficient resourcealgorithms, least spanning tree algorithm. allocations thus decreasing the overall energy consumption and reducing the interferences among1. INTRODUCTION sensor nodes. A large number of clusters will Advances in sensor technology, low-power congest the area with small size clusters and a veryelectronics, and low-power radio frequency (RF) small number of clusters will exhaust the clusterdesign have enabled the development of small, head with large amount of messages transmittedrelatively inexpensive and low-power sensors, from cluster members. In this paper we are going tocalled microsensors[1] The emerging of low power, survey different types of energy efficient andlight weight, small size and wireless enabled sensors coverage efficient wireless sensor network.has encouraged tremendous growth of wirelesssensors for different application in diverse and 2. SURVEYinaccessible areas, such as military, petroleum and 2.1 LEACH [Low Energy Adaptive Clusteringweather monitoring. These inexpensive sensors are Hierarchy][4] and Its Descendantequipped with limited battery power and therefore One of the well known clustering protocolsconstrained in energy [4]. One of the fundamental called LEACH[Low Energy Adaptive Clusteringproblems in wireless sensor network is to maximize Hierarchy][2]. LEACH is a cluster-based protocolnetwork lifetime and time delay in data that includes distributed cluster formation in whichtransmission. Network lifetime is defined as the the nodes elect themselves as cluster heads withtime when the first node is unable to send its data to some probability. The algorithm is run periodicallybase station. Data aggregation reduces data traffic and the probability of becoming a cluster head forand saves energy by combining multiple incoming each period is chosen to ensure that every nodepackets to single packet when sensed data are highly becomes a cluster head at least once within 1/Pcorrelated. In a typical data gathering application, rounds, where P is the predetermined percentage ofeach node sends its data to the base station, that can cluster heads. LEACH organizes its operation intobe connected via a wireless network. These rounds, where each round consists of a setup phaseconstraints require innovative design techniques to where clusters are formed and a steady state phase 712 | P a g e
  2. 2. Priya, Satyesh Sharan Singh, Mukesh Kumar, Rohini Saxena / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.712-719that consists of data communication process. determined. MS-Leach is based on the critical value.LEACH provides significant energy savings and Simulation results clearly show that MS-Leachprolonged network lifetime over conventional outperforms at most by 200% in term of networkmultihop routing schemes, such as the Minimum lifetime. It is proposed as future work itsTransmission Energy (MTE)[2] routing protocol. relationship between multi-hop and single-hop transmissions will be analyzed in-depth in various2.1.1 LEACH-C [5] protocols and new mechanisms of routing will be However, LEACH does not guarantee that developed.the desired number of cluster heads is selected andcluster heads are not evenly positioned across thenetwork. A further improvement of this protocol 2.1.5 LEACH-Heterogeneous [7]known as LEACH-C[4]. In this paper, LEACH-HPR introduced an In LEACH-C, the cluster formation is done energy efficient cluster head election method andat the beginning of each round using a centralized using the improved Prim algorithm to construct analgorithm by the base station. The base station uses inter-cluster routing in the heterogeneous WSN.the information received from each node during the Simulation results show LEACH-HPR is moresetup phase to find a predetermined number of efficient to reduce and balance energy consumptioncluster heads and configures the network into and hence enhance the lifetime of WSNclusters. The cluster groupings are then chosen tominimize the energy required for non-cluster head 2.2 Power-Efficient Gathering in Sensornodes to transmit their data to their respective Information Systems [PEGASIS][8]cluster heads. Results in[4] have shown that the Another clustering protocol which aims tooverall performance of LEACH-C is better than enhance the network lifetime is (PEGASIS)[5].LEACH due to improved cluster formation by the Power-Efficient Gathering in Sensor Informationbase station. Moreover, the number of cluster heads Systems (PEGASIS) uses a greedy algorithm toin each round of LEACH-C is equal to the desired organize nodes into a chain, so that each nodeoptimal value, whereas for LEACH the number of transmits and receives from only one of itscluster heads varies from round to round due to the neighbors. In each round, a randomly chosen nodelack of global coordination among nodes. from the chain will transmit the aggregated data to the base station and reduce the number of nodes that2.1.2 LEACH-Fixed on of cluster[6] communicate directly with the base station. LEACH-F is an algorithm in which thenumber of clusters will be fixed throughout the 2.3Hausdroff Clustering [16]network lifetime and the cluster heads rotated within Authors considered that, once clusterits clusters. Long term phase of LEACH-F is formations take place it’s remaining sameidentical to that of LEACH. LEACH-F have some throughout the network lifetime. This algorithmlimitation because it may or may not be provided maximizes the lifetime of each cluster in order toenergy saving and this protocol does not provide the increase the life time of the system. Cluster life timeflexibility to sensor nodes mobility or sensor nodes can be enhanced by rotating the role of cluster headsbeing removed or added from the sensor networks (CHs) among the nodes in the cluster. Cluster heads selection basically based on the residual energy of2.1.3 LEACH-Energy Threshold [6] the sensor nodes and it also used the proximity of In this cluster will change only when one neighbors as a secondary criterion for enhancingof the following conditions is satisfied: first, Energy energy efficiency and further prolong the networkconsumed by anyone of the cluster head nodes lifetime. The Hausdroff clustering algorithm is(CHs) reach energy threshold (ET) in one round. equally applicable for both uniform and nonuniformSecond, every sensor node should know the energy sensor node initial energy distribution.threshold (ET) value. If in initial phase, anyone ofthe cluster head nodes dies. If any sensor node acts 2.4 PDCH: Pegasis Algorithm Improving Basedas a cluster head node (CHs) in a certain round, it on Double Cluster Head [20]should have the energy dissipated value and Authors proposed an algorithm based oncompares the dissipated value with the energy hierarchical chain topology and this algorithm usingthreshold (ET) value. bottom level cluster head and super level cluster head to improve the load balance. In the hierarchical2.1.4 MS-LEACH [Multi-hop and Single hop- structure, base station (BS) is the center of a circle.Low Energy Adaptive Clustering Hierarchy][6] The BS will predefine the number of levels and In this paper the authors have analyzed the every nodes distance to BS decided the level whichproblem of energy consumption of the single-hop it belongs to. Every node receives the signal fromand multi-hop transmissions in a single cluster. the BS, then according to the signal strength toFinally a critical value of the cluster area size is detect the distance to BS. PDCH outperform to 713 | P a g e
  3. 3. Priya, Satyesh Sharan Singh, Mukesh Kumar, Rohini Saxena / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.712-719PEGASIS algorithm and it is also useful for largenetworks.2.5 Base station Controlled Dynamic Protocol[BCDCP][9] An approach called Base station ControlledDynamic Protocol (BCDCP)[7] is proposed whichproduces clusters of equal size to avoid cluster headoverload and to ensure similar power dissipation ofnodes.2.6 EECS: Energy Efficient Clustering Schemes[12] Authors proposed an algorithm in whichcluster formation is different from LEACH protocol.In LEACH protocol cluster formation takes place onthe basis of a minimum distance of nodes to theircorresponding cluster head. In EECS, dynamicsizing of clusters takes place which is based oncluster distance from the base station. The resultsare an algorithm that addresses the problem thatclusters at a greater distance from the sink requiresmore energy for transmission than those that arecloser. Ultimately it provides equal distribution ofenergy in the networks, resulting in networklifetime. Thus main advantage of this algorithm isthe full connectivity can be achieved for a longerduration. So we can say it provides reliable sensingcapabilities at a larger range of networks for alonger period of time. It provides a 35 percentimprovement in network life time over LEACHalgorithm.2.7 EEUC: Energy Efficient Unequal Clustering[14] This scheme is distance based schemesimilar to EECS and it also required that every nodehas global identification such as its locations anddistances to the base station. Hotspot is the mainproblem in WSNs because of multi hopping thatoccurs when CHs closer to the sink tend to die fastercompare to another node in the WSNS, because theyrelay much more traffic than remote nodes. Thisalgorithms partition the all nodes into clusters ofunequal size, and clusters closer to the sink havesmaller sizes than those farther away from the sink.Thus cluster heads (CHs) closer to the sink canconserved some energy for the inter-cluster dataforwarding. Energy consumed by cluster heads perround in EEUC much lower than that of LEACHstandard but similar to HEED protocol.2.8 BARC: Battery Aware Reliable Clustering[15] Fig-1 Different types of cluster based technique In this clustering algorithm authors usedmathematical battery model for implementation inWSNs. With this battery model authors proposed anew Battery Aware Reliable Clustering (BARC)algorithm for WSNs. It improves the performanceover other clustering algorithms by using Z-MAC 714 | P a g e
  4. 4. Priya, Satyesh Sharan Singh, Mukesh Kumar, Rohini Saxena / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.712-719 and least spanning tree for wireless sensor network to prolong network lifetime and shorten path while and it rotates the cluster heads according to emphasizing energy conservation at the same time.battery recovery schemes. A BARC algorithm Clustering includes partitioning stage and choosingconsists of two stages per round for selection of stage, namely, partitions the multi-hop network andcluster heads: initialization or setup and steady state. then chooses cluster-heads, cluster-head isIn this formation of cluster, take place by electing a responsible for receiving, sending and maintainingset of CHs. BARC enhances the network lifetime information in its cluster. Then all cluster-heads willgreatly compare to other clustering algorithms. construct a least spanning tree to prolong network lifetime ,save energy and shorten path. Simulation2.9 PSO-Clustering [22] results show that the system’s performance have In this paper authors proposed PSO- further improved by using clustering and leastclustering which have four variants of PSO: PSO- spanning tree, It is a promising approach andTVIW (PSO with time varying inertia weight), deserves more future research.PSO-TVAC (PSO with time varying accelerationconstants), HPSO-TVAC (hierarchical PSO-TVAC) 3. MAIN THEORYand PSO-SSM (PSO with supervisor student mode) THE Minimum Spanning Tree (MST)for energy aware clustering in WSNs. This method that is an important and commonlyalgorithm is applicable only when each node has occurring primitive in the design and operation offixed Omni-directional transmission range, the data and communication networks. For instance, insensor field should be mapped into a 2-Dimensional ad hoc sensor networks, MST is the optimal routingspace and nodes are randomly distributed. After tree for data aggregation [2]. Traditionally, thedeployment of the nodes, the nodes are static and efficiency of distributed algorithms is measured bythe positions of the nodes are known to the base the running time and the number of messagesstation. The base station runs the clustering exchanged among the computing nodes, and a lot ofalgorithm and updates nodes about their cluster- research has gone into the design of algorithms thathead and all nodes should have same transmission are optimal with respect to such criteria.ranges and hardware configurations. Cluster based spanning tree can improve lifetime of the network and also gives the shortest2.9.1 PSO-C: Centralized-PSO [23] path for minimum propagation delay. Clustering Authors proposed centralized-PSO includes partitioning stage and choosing stage,algorithms, in which the nodes which have energy namely, partitions the multi-hop network and thenabove average energy resource are elected as the chooses cluster-heads, cluster-head is responsiblecluster heads. In this authors also compare this for receiving , sending and maintaining informationalgorithm with LEACH protocol and with LEACH- in its cluster. Then all cluster-heads will construct aC. Simulation results show that PSO outperform to least spanning tree to prolong network lifetime ,saveLEACH and LEACH-C in term of network life time energy and shorten path. Paper review results showand throughput etc. It also outperforms GA and K- that the system’s performance have furthermeans based clustering algorithms. improved by using clustering and least spanning tree, It is a promising approach and deserves more2.9.2 Distributed PSO[23] future research. Sensors and cluster-heads are PSO control algorithm try to minimize assumed to be stationary or limited moving insideradio power while ensuring connectivity of the clusters. Sensors receive commands from and sendnetwork. In this paper author proposed an important data to its cluster-head, which does pre-processingmetric for a sensor network topology that involve for the data and forward them to other cluster-heads.consideration of hidden nodes and asymmetric links. A cluster-head is located within the communicationIt minimizes the number of hidden nodes and range of all the sensors of its cluster and canasymmetric links at the expense of increasing the communicate with its neighbour cluster-heads.transmit power of a subset of the nodes may in fact Since a cluster-head forwards traffic to other cluster-increase the longevity of the sensor network. Author heads with longer distance as compared to itsexplores a distributed evolutionary approach to sensing nodes, in some applications it is moreoptimize this new metric. Author generates powerful than the sensing nodes in terms of energy,topologies with fewer hidden nodes and asymmetric bandwidth and memory [11,12], while others selectlinks than a comparable algorithm and presents cluster–heads from the deployed sensors [13,14].some results that indicate that his topologies deliver When a cluster-head is under failure due tomore data and last longer. insufficient power, another cluster-head will be selected among the sensors(assume a sensor can2.10. Least Spanning Tree based clustering[21] adjust its transmission power to a larger value (for In this paper, Authors proposed an novel relaying requirement) once it is selected as a cluster-energy-efficient routing protocol based on clustering head. The details on transmission power control 715 | P a g e
  5. 5. Priya, Satyesh Sharan Singh, Mukesh Kumar, Rohini Saxena / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.712-719issues are referenced in for example [15,16]). Thecluster-based architecture raises many interesting 2 2issues such as cluster formation, cluster-head Where di ,j = Xi − XJ + Yi − YJselection and cluster maintenances, which arebeyond the scope of this work. Here, The jth cluster-head as the receiver, the power we only focus on modelling the traffic consumed by this communication is then simply asbehaviour along with the multi-hop cluster-heads by the Eq (4)least spanning tree. The system model consists offive parts: (1) constructing cluster-head part, in each Er (j , i) = er B Ai (4)area dynamic constructing a cluster head accordingto the remainder energy.(2) constructing least By combining Eq. (1) to Eq. (4) we canspanning tree, according to the cluster-head, sink make a cluster-based WSN model. We know thewill dynamic construct least spanning tree to energy consumed at the cluster head is much largerachieve maximum lifetime and prolong network than that at individual sensing node. The reason is aslifetime.(3)sensing part, the sensors around the follows: (1) the cluster-head needs to relay all thetarget area are responsible for probing the traffic of the cluster; (2) for each data unit, thetarget/event and send the collected data to their cluster-head needs to transmit longer distance due tocluster-head; (4) relaying part, the collected data are transmission between clusters, while the sensingrelayed among the cluster-heads by least spanning nodes just transmit data inside the cluster. In view oftree until to the sink; (5) sink, the sink performs this, let Ep and Ec be, respectively, the currentsystem-level data analysis and process for an overall energy and clustering energy(Ec is fixed), after asituation awareness. period of time, the ith cluster-head has transmitsThe energy model based on the given energy information n1 times and has receives informationequation: n2 times before T1(suppose the energy of the ith cluster-head is not lower than the threshold and theEt (i) = (et + ed r n )B (1) information unit is A Erlang ) .the remainder energy of the ith cluster-head at T1 is then simply as the Eq Where et is the energy/bit consumed by the (5) .transmitter electronics (including energy costs of inper strongly dominates other node functions such as n n Ep (i)=Ep (i) – k=1 Et (i , k) - l=1 Et (i , l) - Ec 1 2fact duty cycling due to finite start-up time), and ed ×ni ..(5)accounts for energy dissipated in the transmit op- where i,j,k is respectively denote cluster-head, ni isamp (including op-amp inefficiencies). Both et and the clustering time in cluster i before T1ed are properties of the transceiver used by the By Ep(5),we can compute the remainder energy, ifnodes, r is the transmission range used. The Ep(i) is lower than Ev, then modify the informationparameter n is the power index for the channel path table of the ith cluster-head: set flag=0; broadcastloss of the antenna. B is the bit rate of the radio and information to it’s children, .also inform theis a fixed Topology management provides the neighbor jth cluster-head doesn’t transmitsdistributed parameter in our study information to it, and let ith cluster-head i is in the sleeping state; else the ith cluster-head may go along On the receiving side, a fixed amount of the next clusteringpower is required to capture the incoming radio or transmitting or receiving. According to Primsignal where er is the energy/bit consumed by the algorithm, suppose undirected graph G (V,E,D)receiver electronics used by the node. Typical ,where V is the set of cluster-heads and the numbernumbers for currently available radio transceivers is N, E is the set of connections of cluster-head, andare et= 50× 10-9J/bit, er=50×10-9 J/bit, ed=100× D is the distance of cluster-heads, the process of10-12J/bit/m (for n=2) and B=1 Mbit/s [18]. constructing least spanning tree as illustrated below:  Initializatio:V1=Sink, E′=null, ,and V2=V-V1.Er (j) = er B (2) • Set a edge: which has minimum distance from Sink to one cluster-head (suppose is Vi),where Vi is Now let us consider one-hop directly connected to Sink, then set,V1={Sink,vi},communication in a finite one dimensional network E ′ ={(Sink,vi)} , V2=V2-V1.from the ith cluster-head to the jth cluster-head • For each cluster-head Vk in V1 do :select aacross a distance di,j. If the ith cluster-head will minimum distance dk,j,which Vk∈V1,Vj∈ V2 andgenerate A Erlang and the distance of the ith cluster- e′=(Vk,Vj) ∈E ,but is not∈E′, then V1=V1∪Vj,head and the jth cluster-head is dij,so the power E′={(Vk,Vj)} ∪e′, V2=V2-Vj.consumed by this communication is then simply as • if V2 is empty then end, else go to (3).the Eq. (3). Et (i , j) = (et + ed dnj ) B Ai i (3) 716 | P a g e
  6. 6. Priya, Satyesh Sharan Singh, Mukesh Kumar, Rohini Saxena / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.712-719 Sink Sink (a)The least spanning tree before (b)The least spanning tree after Re-clustering Re-clusteringFig-2 The least Spanning TreeWhen a cluster-head’s energy is lower than REFERENCESthreshold, then first renewably select a node as newcluster-head in the cluster, second renewably [1] I.F. Akyildiz, W. Su, Y.execute constructing least spanning tree algorithm, Sankarasubramaniam,(2000) E.so a new constructing least spanning tree has Cayirci,Wireless sensor networks: aconstructed, all sensing information can be send to survey, Computer Networks 38 393–422.J.Sink along the new least spanning tree, this Clerk Maxwell, A Treatise on Electricityalgorithm can efficient shorten path and prolong and Magnetism, 3rd ed., vol. 2. Oxford:network lifetime. As illustrated in Fig.1. Fig.1(a) Clarendon, 1892, pp.68–73.show the initial least spanning tree, after some time [2] M. Ilyas, I. Mahgoub,(2000) Handbook of,if the power of C1’s cluster head is lower threshold Sensor Networks:Compact Wireless and,nodes in C1 will execute re-clustering to choose a Wired Sensing Systems, CRC Press,Newnew cluster-head, this time system will execute York .constructing least spanning tree algorithm, and make [3] W. Ye, J. Heidemann, D. Estrin,(2000)a new least spanning tree as Fig.1(b).we can know Medium access control with coordinatedthe total-path of new least spanning tree is shorter adaptive sleeping for wireless sensorthan old least spanning tree. networks, IEEE/ACM Transactions on Networking 12 (3) 493–506.3. CONCLUSION [4] W.B. Heinzelman, A. Chandrakasan, H. Balakrishnan,(2000)Energy effcient From the literature review of cluster based communication protocol for wirelessMinimum Spanning Tree and other cluster based microsensor networks, in: IEEE Hawaii Int.algorithm we have a lot of advantages of cluster Conf. on System Science, Hawaii, USA,,based Minimum Spanning Tree over other pp. 1–10.algorithm. Since with cluster based Minimum [5] W. R Heinzelman, A. P Chandrakasan, andSpanning Tree we can add more application of other H. Balakrishnan,(2000),algorithm such as power gathering and distributed “Energyefficient communication protocolleast spanning tree. By these applications we can for wireless microsensor networks,” inimprove the efficiency of WSN and also reduce the Proceedings of the 33rd Hawaiipower delay of the information and increase the International Conference on Systemrange of sensor nodes. Sciences. 717 | P a g e
  7. 7. Priya, Satyesh Sharan Singh, Mukesh Kumar, Rohini Saxena / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.712-719[6] I. F. Akyilldiz, W. Su, Y. Hawaii International Conference on System Sankarasubramaniam and E. Cayirci, Sciences. (2002), “A survey on sensor networks,” [17] S.Lindsey,C.S.Raghavendra, (2004) IEEE Communications Magazine, pp. PEGASIS:power efficient gathering in 102−114. sensor information systems, in: Proc. of the[7] W. B Heinzelman, A. P Chandrakasan, and IEEE Aerospace Conference, Big Sky, H. Balakrishnan,(2002), “An application- Montana . specific protocol architecture for wireless [18] M. Kubisch, H. Karl, A. Wolisz, L. Zhong, microsensor networks,” IEEE Transactions J. Rabaey,(2004) Distributed algorithms for on Wireless Communications, vol. 1, no. 4, transmission power control in wireless pp. 660-70. sensor networks, in: IEEE Wireless[8] S. Lindsey, C.S. Raghavendra,(2001) Communications and Networking PEGASIS: power efficient gatheringin Conference (WCNC04), New Orleans . sensorinformationsystems,in: [19] V. Kawadia, P.R. Kumar, (2004)Principles IEEEAerospace Conf., Montana, Canada, and protocols for power control in ad hoc pp. 1–6. networks, IEEE J. Select. Areas Commun.[9] S.J. Baek, G. Veciana, X. Su,(2002) 23 (1)76–88. Minimizing energy consumption in [20] J. Haapola, Z. Shelby, C.A. Pomalaza- largescale sensor networks through Ra′ez, P. Ma¨ho¨nen,(2005) Cross layer distributed data compression and energy analysis of multi-hop wireless hierarchical aggregation, IEEE Journal on sensor networks, in:Proceedings of the Selected Area in Communications 22 (6) European Workshop on Wireless Sensor 1130–1140. Networks, Istanbul, Turkey.[10] Wei-Tsung Su , Ko-Ming Chang, Yau- [21] Q.Gao,K.J.Blow,D.J.Holding et,(2007) Hwang Kuo, (2002)eHIP: An Radio range adjustment for energy efficient energyefficient hybrid intrusion prohibition wireless sensor networks[EB/OL]. system for cluster-based wireless sensor www.elsevier.com /locate/adhoc, in: Ad networks, Computer Networks 51 1151– Hoc Networks 42006,75–82. 1168. [22] J. Kennedy and R. C. Eberhart, “Particle[11] A. Manjeshwar, D.P. Agrawal,(2002) swarm optimization, (1995),” IEEE TEEN: a routing protocol or enhanced International Conference on Neural efficiency in wireless sensor networks, in: Networks, vol.4, pp. 1942-1948, Perth, 15th IEEE Parallel and Distributed Australia. Processing Symposium, San Francisco, [23] X. Co, H. Zhang, J. Shi, and G.Cui USA, pp. 2009–2015. “Cluster heads election analysis for multi-[12] Jain-Shing Liu , Chun-Hung Richard Lin, hop wireless sensor networks based on (2002) Energy-efficiency clustering weighted graph and particle swarm protocol in wireless sensor networks. Ad optimization”. In IEEE fourth International Hoc Networks 3 371– 388. Conference on computing, 7, 599–603.[13] Shensheng Tang, Wei Li,(2002) QoS supporting and optimal energy allocation for a cluster based wireless sensor network. Computer Communications , pp:2569– 2577.[14] M. Younis, M. Youssef, K. Arisha,(2002) Energy-aware routing in clusterbased sensor networks, in: Proc. of the 10th IEEE/ACM Sym. onModeling, Analysis and Simulation of Computer and TelecomSystems (MASCOTS’02), Fort Worth, TX.[15] L. Subramanian, R.H. Katz,(2004) An architecture for building self configurable systems, in: Proc. of IEEE/ACM Workshop on Mobile Ad Hoc Networking and Computing, Boston, MA.[16] W.R. Heinzelman, A. Chandrakasan, H. Balakrishnan,(2004) Energy-efficient communication protocol for wireless sensor networks, in Proc. of the 33rd 718 | P a g e
  8. 8. Priya, Satyesh Sharan Singh, Mukesh Kumar, Rohini Saxena / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 3, Issue 1, January -February 2013, pp.712-719BIOGRAPHIES Priya is PG Student in the Department of Electronics & Communication Engineering in SHIATS, Allahabad. She received her B.Tech. Degree in Electronics Communication System Engineering from SIET, GreaterNoida in 2007. She is pursuing M.Tech in Wirelesscommunication Engineering in SHIATS, Allahabad.Her research is focused on Wireless Sensor Networkand Computer Networks. Satyesh Sharan Singh is PG Student in the Department of Electronics & Communication Engineering in SHIATS, Allahabad. He received his B.Tech. Degree in Electronics and Communication Engineering from SIET, Greater Noida in 2007.Hehas three year industrial experience in navigationfield. He is pursuing M.Tech in WirelessCommunication Engineering in SHIATS,Allahabad. His research is focused on WirelessSensor Network and Computer Networks. Mukesh Kumar is working as a Asst. Prof. in the Department of Electronics & Communication Engineering in SHIATS, Allahabad. He received his M.Tech. Degree in Advanced Communication SystemEngineering from SHIATS, Allahabad in 2010. Hisresearch is focused on Wireless Sensor Network andComputer Networks Microwave Engineering, aswell as Optical fiber communication. Rohini Saxena is working as a Asst. Prof. in the Department of Electronics & Communication Engineering in SHIATS,Allahabad. She received her M.Tech. Degree inAdvanced Communication System Engineeringfrom SHIATS, Allahabad in 2009. Her research isfocused on Microwave Engineering, WirelessSensor Network and Computer Networks andMobile communication. 719 | P a g e

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