International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volu...
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volu...
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volu...
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volu...
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volu...
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volu...
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Energy efficient k target coverage in wireless sensor net-2

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Energy efficient k target coverage in wireless sensor net-2

  1. 1. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 3, May – June (2013), © IAEME254ENERGY EFFICIENT K-TARGET COVERAGE IN WIRELESSSENSOR NETWORKAnurag11(School of Computer Engineering, Kalinga Institute of Industrial Technology/ KIITUniversity , KIIT Campus, Patia, Bhubaneshwar, India)ABSTRACTSensing and monitoring a natural phenomenon or target by deploying the sensornodes with minimum consumption of energy is a quest for the researchers in designing thetopology of the wireless sensor network. Many proposals have illustrated in the literature,which are specific in nature and are not optimally feasible, in developing a framework for thedesign of appropriate clusters of sensing nodes by considering both their sensing capacity andenergy efficiency. For monitoring any inhospitable environment, sensors are being droppedrandomly from an aircraft and hence they do not fall on precise location. More sensors getclusters at one location as compare to another. Sometimes the data sensed are being noisy andthe sensors are being vulnerable to failure, hence more number of sensors often required tocover a particular target. In this paper, we have proposed an energy efficient method to coverthe target with less number of sensor nodes to limit their energy, in which each target has tobe covered by exactly k sensors out of a cluster of n sensor nodes. The collected data passesto the supervisor node of the respected clusters and supervisor nodes cooperatively send thedata to the sink from there it is available to the user for its further utilization.Keywords: Dijktra’s algorithm, Energy consumption formula, K-coverage, Relay Node,Wireless Sensor Network.1. INTRODUCTIONWireless Sensor Network is an evolving research field. It has a numerous applicationin varieties of fields like civil, military, industrial, agricultural, indoor environmentalmonitoring, antique protection [1] and health application[2] to name a few .A WSN usuallyconsists of large number of sensor nodes for sensing and monitoring the information .ThisINTERNATIONAL JOURNAL OF COMPUTER ENGINEERING& TECHNOLOGY (IJCET)ISSN 0976 – 6367(Print)ISSN 0976 – 6375(Online)Volume 4, Issue 3, May-June (2013), pp. 254-259© IAEME: www.iaeme.com/ijcet.aspJournal Impact Factor (2013): 6.1302 (Calculated by GISI)www.jifactor.comIJCET© I A E M E
  2. 2. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 3, May – June (2013), © IAEME255sensor nodes after sensing sends the sensed information to the base station for processing andfrom there, it is available to the internet for the end user [3].One of an important task of the wireless sensor network is the coverage. Coverage deals withhow efficiently a specific region of interest is being covered by the sensors. The goal is tohave the region of interest being monitored by at least one sensor node. The coverageproblem is being broadly classified into the following three types.1. Target coverage: the goal is to monitor the sets of targets in a region2. Area coverage: the goal is to monitor the specific area[4].3. Barrier coverage: the goal is to detect all intrusion in the barrier of the sensor network[5].To monitor the sets of targets in an area, the sensors are being deployed randomly inan area. The coverage of a target by a single sensor in not beneficial sometimes because thesensor are more prone to failure due to harsh environmental condition, energy depletion ormalicious attack[6].Hence it required that a target must be covered by k no. of sensors inwhich k≥1. In this paper, we will keep some sensors to sleep mode to save energy to someextent and hence the target is being covered by exactly k-sensors. We then select a supervisornode .This supervisor node passes the data to the nearest supervisor node successively, andfinally cooperatively, the data is being transferred to the sink.Various researches have been done till now related to the target area coverage. In [7],k-target coverage is being proposed in which a supervisor node is being selected such that ithas the responsibility to monitor the entire k-1 target in an area. This supervisor nodeprocesses the data and sends the result cooperatively to the sink. In [8], the Greedy MSCHeuristic is being proposed in which the critical target and critical sensor is being selectedwhich has the responsibility to monitor all the target. This Greedy –MSC proves to be NP-Complete and has the complexity O(iM2N), where there are M targets and N sensors. In[4],an algorithm for the non-disjoint set cover is being proposed in which only those target isbeing covered by the sensor which is more closer to the sensor to save the energy to someconsiderable extent. In [9],TPISC algorithm is being proposed which works in three phase: Inthe first phase, set cover is being constructed which has the responsibility to monitor all thetarget. Connectivity to the set –cover is being maintained in the second phase and in the finalstage ,we remove the redundant sensor. In [10],a greedy based algorithm has been proposedin which a critical target has been selected from the target sets and the unique route from thesensor set to the sink is being determined by using the Shortest path Tree. This techniqueproves to be NP-Complete. In [11], grid based strategies have been proposed in which eachpoint in a grid must be filled with probability at least T and which the no. of sensors at leastk. In [12],a heuristic algorithm has been proposed which deals with multiple target coverageproblem. There are large number of overlapped target in a region and their correspondingoverlapped sensors. For each overlapped sensor, we have to select the Responsible sensor.This responsible sensor has the responsibility to transfer the data of overlapped target to thesink node. RSSA algorithm will then executed in which the number of target observed byeach Overlapped sensor except Responsible sensor has been reduced by one. The complexityof RSSA algorithm has been given by O(MN) while the complexity of heuristic algorithm hasbeen given by O(jM2N) were M and N are targets and sensors respectively.The rest of the paper is being organized as follows: Section 2 contains our problemformulation. We describe our proposed work in Section 3 and pseudo code in section 4.Finally, in section 5, we conclude our paper.
  3. 3. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 3, May – June (2013), © IAEME2562. PROBLEM FORMULATIONWe considered the following scenario: large no. of sensors is being deployed in anarea with close proximity of the targets. The sensors are being densely deployed around thetargets. Each sensor has limited battery life and hence is not being rechargeable in most of thecases. So, energy conservation is being a critical issue in these circumstances. We have theassumption that the number of sensors deployed in the field is much greater that the optimalnumber to perform the sensing tasks. The sensors have uniform sensing range. Each sensor isaware of the location using localization technique.A sensor which does the tasks of sensing and monitoring is called source sensor andsensor which does not perform the sensing tasks and does the tasks of data forwarding arecalled relay sensors. The sensor which does sensing and relaying tasks are the active sensors.Rest of the sensors will be in sleep mode in order to conserve energy.We assume that all the source sensors have the same data generation rate for a targeti.e. all the source sensors uses the same sampling frequency, quantization, modulation andcoding scheme for each target .Therefore a fixed amount of bit, denoted by β called coveragerate, is generated by each source sensor for a target in a second.2.1. Sensing Energy consumption modelThe energy consumed in transmitting a bit of data from node i to node j is give by:Where and b are constants and is the Euclidian distance between i and j.α is the pathloss factor , be the energy consumed in receiving a bit of data and be the energyconsumed in sensing a target for a bit of data. Let be the number of targets a sensor scan monitors them for t seconds. If Coverage rate is β, the energy consumed in by the sourcesensor for t second is the sum of sensing and transmission energy. So, the energy consumedby the source sensor i which monitors target for t seconds to and transmits themonitored information to the node j would be:E(i,t)=β. (t) + i ϵ Ss and i SrA relay nodes receives the data from the sensors and transmits them to the other supervisornodes .For a given supervising nodes i, let denotes the number of target in whichsupervising node i relay the data for seconds. The energy consumed by the sensing nodes isthe sum of sensing energy and transmitting energy. So, the energy consumed in the relaynode i which transfers the traffic to the other relay node j for t seconds would beE(i,t)= i Ss and i ϵ SrA relay node receives data from one relay sensor and transmits them to the other relay sensor.For a given relay node i, (t) denotes the number of targets which node i relay the data for tsecond.Our proposed model is based upon this method.
  4. 4. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 3, May – June (2013), © IAEME2573. PROPOSED WORKThere is large number of cluster-set for each target, in which each target is beingcovered by set of power-constrained sensors. Our aim is to implement an energy–efficientmechanism for k target coverage in which each targets must be covered by the set of sensorsfor longer duration. The network lifetime is being defined as the time in which there existsany one target which can’t be monitored by any sensor.Our objective function is to maximize the lifetime of each cluster in the network.Fig: A k-Target coverage scenario in which k=4We have use Dijktra’s algorithm to calculate the all pair-shortest path between eachrelay node with the complexity of O(|E|)..It is mainly applicable for the dense network and isthe faster than any other algorithm with the shortest time complexity. The edge between themrepresents the energy consumed in transferring the data from one relay node to the other.A directed graph between the relay sensors pair is being formed in which each edgerepresents the energy consumed in transmitting the data.Our proposed method work as follows: Initially, all the sensors are in sleep mode .Westarts activating all the sensors and the sensors starts covering the target. Large number ofclusters formation takes place for each target. A target is being covered by more than k-sensors .To save the energy of the sensor; we have to put some of the sensors of lower energyto the sleep mode in order to conserve energy such that each target is being covered byexactly k-sensors. The source sensors are already sensing and sending the sensed data byeach source sensor nodes consumes lots of energy, so a sensor called relay sensor is beingselected, this has the responsibility to send the data to the nearest relay sensor of anothercluster. Out of this k -active sensor nodes, we select the sensor with the highest energy asrelay node to save the power to some considerable extent. The Dijktra’s algorithm is beingexecuted between each relay nodes and the shortest path between each relay nodes getsobtained. This route has the responsibility to send the data to the sink.
  5. 5. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 3, May – June (2013), © IAEME258When the any of the sensor in the cluster dies, we check the nearest sensor which is in sleepmode and have higher energy. That sensor will be added to that cluster. Finally, we record thenetwork-lifetime, target covered and the cluster set C1, C2,, …. , CN.4. PSEUDO-CODE1.% Initialization%2.set l=0;3.set Ss=S,j=04.set l=1;5.while each target is being covered by at least k-sensor in Ss do6. % make a cluster set Cj7.Set j=j+1;Cj=φ and St=T8. for each tϵSt9. b(t)≥k10. for each Si ϵ Cj11.we keep only the nearest k sensor of higher value of E(i,t) to be in active mode untilb(t)=k;12.dijktra’s algorithm is executed between each of the k sensors13.for each cluster Ci, we select the relay node RN which has higher energy14.compute dijktra’s algorithm between each RN ϵC and find the shortest route between eachrelay sensor.15.for every si ϵCj ,16. lifetime_si=lifetime_si-w17. if lifetime_si≤018. Cj=Cj-{si}19. we add the nearest sensor of sleep mode which is of higher value of Energy20. Cj=Cj U si21. end if22 end for23 end for24 end for25 end for26. end while27. Return cluster set C1,C2,…,CN and the target coveredHere, b(t) denotes no. of sensors covering a single target . RN is the set of relaynodes.5. CONCLUSIONIn this paper, we have addressed the k-target coverage problem. It increases thelifetime of the sensor network to some extent by selecting a supervisor node and transmittingthe sensed data to the nearest supervising node to save energy to considerable extent .We willimplement our proposed work by MATLAB in the next section. We may also apply geneticalgorithm to for its further modification. However, more work has to be done in this field sothat global solution can be achieved.
  6. 6. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 – 6375(Online) Volume 4, Issue 3, May – June (2013), © IAEME259REFERENCES[1] Yunyue Lin and Qishi Wu,” Approximate Algorithms for Sensor Deployment with k-coverage in Constrained 3D Space”, in 16th International Conference on Parallel andDistributed Systems”, 2010[2] Nahar Sultana, Ki-moon Choi and Eui-nam Huh,” Mobility Support Secure CoverageProtocol for Monitoring Applications using Wireless Sensor Networks”,in InternationalConference on Computational Sciences and Its Applications ICCSA 2008,2008[3] Purnima Khuntia and Prasant Kumar Pattnaik,” Some Target Coverage Issues ofWireless Sensor Network”, International Journal of Instrumentation, Control & Automation(IJICA), Volume 1, Issue 1, 2011[4] PURNIMA KHUNTIA, PRASANT KUMAR PATTNAIK,” TARGET COVERAGEMANAGEMENT PROTOCOL FOR WIRELESS SENSOR NETWORK”, Journal ofTheoretical and Applied Information Technology” 15th January 2012. Vol. 35 No.1[5] Ehsan Saradar Torshizi, Saleh Yousefi and Jamshid Bagherzadeh,” Life TimeMaximization for Connected Target Coverage in Wireless Sensor Networks with SinkMobility, in 6th International Symposium on Telecommunications, 2012[6] Gao Jun Fan, Feng Liang and ShiYao Jin,” An Efficient Approach for Point CoverageProblem of Sensor Network”,in International Symposium on Electronic Commerce andSecurity, 2008[7] S.Omid Melli,” K-Target Coverage & Connectivity in Wireless Sensor NetworkConsidering the angle coverage”,IEEE,2011.[8] Mihaela Cardei ,My T. Thai ,Yingshu Li and Weili Wu,” Energy-Efficient TargetCoverage in Wireless Sensor Networks”, IEEE INFOCOM 2005[9]Mohammad ali Jamali, Navid Bakhshivand, Mohammad Easmaeilpour and DavoodSalami,” AN ENERGY –EFFICIENT ALGORITHM FOR CONNECTED TARGETCOVERAGE PROBLEM IN WIRELESS SENSOR NETWORKS”,IEEE,2010.[10] Yong-hwan Kim,Youn-Hee Han, Chang-min Mun,Chan Yeol Park and Doo-Soon, Park,”Lifetime Maximization Considering Connectivity and Overlapped Targets in WirelessSensor Networks”,IEEE,2010[11] Wenzheng Zhang and Chuanlin Zhang,” Sensor Placement for Grid Coverage withProbability Mode” ,IEEE,2010[12] Sung-Yeop Pyun and Dong-Ho Cho,” Power-Saving Scheduling for Multiple-TargetCoverage in Wireless Sensor Networks”, IEEE COMMUNICATIONS LETTERS, VOL. 13,NO. 2, FEBRUARY 2009[13] S.R.Shankar and Dr.G.Kalivarathan, “Feasibility Studies of Wireless Sensor Networkand its Implications”, International Journal of Electrical Engineering & Technology (IJEET),Volume 4, Issue 2, 2013, pp. 105 - 111, ISSN Print : 0976-6545, ISSN Online: 0976-6553.[14] Neeraj Tiwari, Rahul Anshumali and Prabal Pratap Singh, “Wireless Sensor Networks:Limitation, Layerwise Security Threats, Intruder Detection”, International Journal ofElectronics and Communication Engineering & Technology (IJECET), Volume 3, Issue 2,2012, pp. 22 - 31, ISSN Print: 0976- 6464, ISSN Online: 0976 –6472.[15] Revathi Venkataraman, K.Sornalakshmi, M.Pushpalatha and T.Rama Rao,“Implementation of Authentication and Confidentiality in Wireless Sensor Network”,International Journal of Computer Engineering & Technology (IJCET), Volume 3, Issue 2,2012, pp. 553 - 560, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375.

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