Computer Science ›› 2017, Vol. 44 ›› Issue (2): 123-128, 146.doi: 10.11896/j.issn.1002-137X.2017.02.018

Previous Articles     Next Articles

Robust Approach for Holes Recovery of Wireless Sensor Networks

YAN Luo-heng and HE Yu-yao   

  • Online:2018-11-13 Published:2018-11-13

Abstract: In the wireless sensor hybrid networks composed of stationary nodes and mobile nodes,coverage holes is one of the key problems because it directly reduces the performance of network.In order to solve this problem,a robust approach based on improved artificial fish swarm algorithm was presented for holes recovery in this paper.The movement of mobile nodes is analogized to the motion of artificial fish such as prey,follow and swarm with the network coverage as object function.Two new fish motions called as jump and rebirth are also presented to enhance the convergence of this algorithm.The self-adaptive visual distance and step size of fish are implemented when the status of artificial fish is updated to recover the hole of networks.Simulation experiments show the robustness of the algorithm.The holes can be recovered efficiently without location information and holes probe using the least amount of mobile nodes.The network coverage is improved significantly with this proposed algorithm.

Key words: Wireless sensor networks,Hybrid network,Holes recovery,Artificial fish swarm algorithm,Robustness

[1] WANG L,GUO Y,ZHAN Y.Security topology control method for wireless sensor networks with node-failure tolerance based on self-regeneration[J].Eurasip Journal of Wireless Communications and Networking,2010(1):1-11.
[2] LIU M,CAO J N,ZHENG Y,et al.Analysis for multi-coverage problem in wireless sensor networks[J].Journal of Software,2007,18(1):127-136.(in Chinese) 刘明,曹建农,郑源,等.无线传感器网络多重覆盖问题分析[J].软件学报,2007,18(1):127-136.
[3] BEJERANP Y.Simple and efficient k-coverage verification without location information [C]∥Proceedings of the IEEE Confe-rence on Computer Communications.Phoenix,2008:291-295.
[4] KUMAR S,LAI T H,BALOGH J.On k-coverage in a mostly sleeping sensor network[C]∥Proceedings of the 10th Annual International Conference on Mobile Computing and Networking.Philadelphia,PA,USA,2004:144-158.
[5] NITIN K,DIMITRIOS G.Sensor network coverage restoration [J].CITESEER,2008,10(12):21-24.
[6] LI X,DAVID H.Distributed coordinate-free hole recovery[C]∥Proc.of GLOBECOM.Beijing,2006:189-194.
[7] XU P F,CHEN Z G.Distributed voronoi coverage algorithm in wireless sensor networks[J].Journal on Communications,2010,31(8):25-34.(in Chinese) 徐鹏飞,陈志刚.无线传感器网络中的分布式 Voronoi覆盖控制算法[J].通信学报,2010,31(8):25-34.
[8] WANG G,CAO G,PORTA T.Movement-assisted sensor de-ployment[J].IEEE Transaction on Mobile Computing,2006,5(6):640-652.
[9] YANG K,LIU Q,ZHANG S K,et al.Holerecovery algorithm based on mobile inner nodes in wireless sensor networks [J].Journal on Communications,2012,33(9):116-117.(in Chinese) 杨凯,刘全,张书奎,等.利用移动内点来修复传感器网络空洞的算法[J].通信学报,2012,3(9):116-117.
[10] WANG G,CAO G,BERMAN P,et al.Bidding protocols for deploying mobile sensors [J].IEEE Transactions on Mobile Computing,2007,6(5):563-576.
[11] WANG L M,LI F,QIN Y.Resilient method for recovering co-verage holes of wireless sensor networks by using mobile nodes [J].Journal on Communications,2011,32(4):1-8.(in Chinese) 王良民,李菲,秦颖.基于移动节点的无线传感器网络覆盖洞修复方法[J].通信学报,2011,32(4):1-8.
[12] SU H,WANG Y.A self-healing algorithm without location in sensor networks[J].Chinese Journal of Computers,2009,32(10):1957-1970.(in Chinese) 苏瀚,汪芸.传感器网络中无需地理信息的空洞填补算法[J].计算机学报,2009,32(10):1957-1970.
[13] JIANG D.Research on the discovery and restoration of blind spots in wireless sensor networks[D].Shenyang:Northeastern University,2008.(in Chinese) 蒋丹.无线传感器网络覆盖盲区的发现与修复方法研究[D].沈阳:东北大学,2008.
[14] YAN F,MARTINS P,DECREUSEFOND L.Accuracy of homology based coverage hole detection for wireless sensor networks on sphere [J].IEEE Transactions on Wireless Communications,2014,3(7):3583-3595.
[15] DAI G Y,CHEN L Y,ZHOU B B,et al.Coverage hole detection algorithm based on Voronoi diagram in wireless sensor work [J].Journal of Computer Application,2015,35(3):620-623.(in Chinese) 戴国勇,陈麓屹,周斌彬,等.基于Voronoi图的无线传感器网络覆盖空洞检测算法[J].计算机应用,2015,35(3):620-623.
[16] WANG R,LIU G Z.Wireless sensor network deployment based on fish-swarm optimization algorithm[J].Journal of Vibration and Shock,2009,28(2):8-11.(in Chinese) 王蕊,刘国枝.基于鱼群优化算法的无线传感网络部署[J].振动与冲击,2009,28(2):8-11.
[17] ZOU Y,CHAKRABARTY K.Sensor deployment and target localization in distributed sensor networks [J].ACM Transactions on Embedded Computing Systems,2004,3(1):61-91.
[18] HONG H H.Research on solving method of coverage area in wireless sensor networks [D].Haibin:Haibin Institute of Technology,2015.(in Chinese) 洪浩瀚.无线传感器网络覆盖面积求解方法研究[D].哈尔滨:哈尔滨工业大学,2015.
[19] LI X L,SHAO Z J,QIAN J X.An optimizing method based on autonomous animates:fish-swarm algorithm [J].Systems Engineering Theory and Practice,2002(11):32-38.(in Chinese) 李晓磊,邵之江,钱积新.一种基于动物自治体的寻优模式:鱼群算法 [J].系统工程理论与实践,2002(11):32-38.
[20] 江铭炎,袁东风.人工鱼群算法及其应用[M].北京:科学出版社,2012 .

No related articles found!
Full text



[1] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75, 88 .
[2] XIA Qing-xun and ZHUANG Yi. Remote Attestation Mechanism Based on Locality Principle[J]. Computer Science, 2018, 45(4): 148 -151, 162 .
[3] LI Bai-shen, LI Ling-zhi, SUN Yong and ZHU Yan-qin. Intranet Defense Algorithm Based on Pseudo Boosting Decision Tree[J]. Computer Science, 2018, 45(4): 157 -162 .
[4] WANG Huan, ZHANG Yun-feng and ZHANG Yan. Rapid Decision Method for Repairing Sequence Based on CFDs[J]. Computer Science, 2018, 45(3): 311 -316 .
[5] SUN Qi, JIN Yan, HE Kun and XU Ling-xuan. Hybrid Evolutionary Algorithm for Solving Mixed Capacitated General Routing Problem[J]. Computer Science, 2018, 45(4): 76 -82 .
[6] ZHANG Jia-nan and XIAO Ming-yu. Approximation Algorithm for Weighted Mixed Domination Problem[J]. Computer Science, 2018, 45(4): 83 -88 .
[7] WU Jian-hui, HUANG Zhong-xiang, LI Wu, WU Jian-hui, PENG Xin and ZHANG Sheng. Robustness Optimization of Sequence Decision in Urban Road Construction[J]. Computer Science, 2018, 45(4): 89 -93 .
[8] LIU Qin. Study on Data Quality Based on Constraint in Computer Forensics[J]. Computer Science, 2018, 45(4): 169 -172 .
[9] ZHONG Fei and YANG Bin. License Plate Detection Based on Principal Component Analysis Network[J]. Computer Science, 2018, 45(3): 268 -273 .
[10] SHI Wen-jun, WU Ji-gang and LUO Yu-chun. Fast and Efficient Scheduling Algorithms for Mobile Cloud Offloading[J]. Computer Science, 2018, 45(4): 94 -99, 116 .