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Sweep Coverage中的节点移动控制 被引量：5

Controlling the mobility of sensors in Sweep Coverage
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摘要 作为无线传感器网络中一种新的覆盖类型,Sweep Coverage与其他覆盖类型相比,可以使用较少的节点满足特定区域的监控需求.为了改进Sweep Coverage机制的性能,本文以Vehicle Routing Problem with Time Windows问题的模型,对Sweep coverage问题进行了分析,提出了一种基于模拟退火算法的Sweep Coverage机制(VRP-Sweep).实验结果表明,在相同的网络场景下,VRP-Sweep机制较以往的Sweep Coverage机制取得更好的性能表现. Sweep Coverage is a new kind of coverage scenario, in which sensors are requested to monitor Points of Interest （POI） within certain time interval. The key issue of Sweep Coverage Scheme is to schedule the sensors, mobility effectively. In this work, the authors first analyze Sweep Coverage problem with VRPTW model, then propose a novel coverage scheme（VRP-Sweep） based on Simulated An- nealing algorithm. Simulation results show that VRP-Sweep scheme achieves better performance than existing schemes.
作者 王伟 林锋 周激流
机构地区 四川大学计算机学院
出处 《四川大学学报（自然科学版）》 CAS CSCD 北大核心 2010年第5期1015-1019,共5页 Journal of Sichuan University(Natural Science Edition)
基金 国家自然科学基金(60773168)
关键词 无线传感器网络 覆盖机制 SWEEP COVERAGE 移动控制 模拟退火 wireless sensor networks, Coverage Scheme, Sweep Coverage, mobility control, simulated annealing
分类号 TN92 [电子电信—通信与信息系统]
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参考文献10

  • 1Bai X, Kumar S, Xuan D, et al. Deploying wireless sensors to achieve both coverage and conneetivity[C] //Proceedings of the 7th ACM international symposium on Mobile ad hoe networking and computing, Florence, 2006. New York: Association for Computing Machinery, 2006.
  • 2Hdeeda M, Bagheri M. Efficient k-coverage algorithms for wireless sensor networks[R]. Burnaby: School of Computing Science, Simon Fraser University, 2006.
  • 3Zhang H, Hou J C. Maintaining sensing coverage and connectivity in large sensor networks[J]. Journal on Wireless Ad Hoe and Sensor Networks, 2005, 1(1-2) : 89.
  • 4Kumar S, Lai T H, Arora A. Barrier coverage with wireless sensors[C]//Proceedings of the 11th annual international conference on Mobile computing and networking, Cologne, 2005. New York: ACM, 2005.
  • 5Liu B Y, Dousse O, Wang J, et al. Strong barrier coverage of wireless sensor networks [C] // Proceedings of the 9th ACM international symposium on mobile adhoc networking and computing. New York:ACM, 2008.
  • 6Cheng W F, Li M, Liu K, et al. Sweep coverage with mobile sensors[C]//IEEE international symposium on parallel and distributed processing. Washington DC: IEEE Computer Society, 2008.
  • 7Braysy M, Michel G. Vehicle routing problem with time windows: Part II[J]. Transportation Science, 2005, 39(1): 119.
  • 8Br-iysy M, Michel G. Vehicle routing problem with time windows: Part I[J]. Transportation Science, 2005, 39(1): 104.
  • 9Solomon M. Algorithms for the vehicle routing and scheduling problems with time window constraints [J]. Operations Research,1987, 35(2): 254.
  • 10丁跞,周激流,林锋.基于NS的DT-MSN实验床设计和实现[J].四川大学学报（自然科学版）,2009,46(1):57-60. 被引量：5

二级参考文献5

  • 1Jain S, Fall K, Patra R. Routing in a delay tolerant network[C]. Portland: ACM, 2004: 145.
  • 2Fall K. A delay-tolerant network architecture for challenged internets[C]. Karlsruhe Germany: ACM, 2003 : 27.
  • 3Juang P, Oki H, Wang Y. Energy-efficient computing for wildlife tracking, design tradeoffs and early experiences with zebranet[C]. San Jose: ASPLOSX, 2002: 96.
  • 4Lin F, Wang Y, Wu H Y. Testbed implementation of delay/fault-tolerant mobile sensor network (DFTMSN) [C]. Pisa Italy: IEEE, 2006:321.
  • 5Fall K, Hong W, Madden S. Custody transfer for reliable delivery in delay tolerant networks [R]. Berkeley: Intel Research, 2003.

共引文献4

同被引文献43

  • 1BAI Xiao-le; XUAN Dong, YUN Zi-qiu, et al. Complete optimal de- ployment patterns for full-coverage and k-connectivity( k ≤6) wireless sensor networks [ C ]//Proe of the 9th ACM International Symposium on Mobile Ad hoc Networking and Computing. New York :ACM Press, 2008 : 401-410.
  • 2YANG Guan-qun,QIAO Da-ji. Barrier information coverage with wire- less sensbrs[ C]//proc of IEEE Conference on Computer Communica- tions. 2009:918 -926.
  • 3CHENG Wei-fang, LI Mo, LIU Ke-bin, et al. Sweep coverage with mo- bile sensors [ C ]//Proc of IEEE International Symposium on Parallel and Distributed Processing. Washington DC : tEEE Computer Society, 2008 : 1-9.
  • 4JAIN A. Data clustering: 50 years beyond K-means [J]. Pattern Recognition Letters ,2010,31 ( 8 ) :651-666.
  • 5PELLEG D, MOORE A. X-means: extending K-means with efficient estimation of the number of dusters [ C ]//Proe of the 17thiInterna- tional Conference on Machine Learning. San Franeiseo: Morgan Kauf- mann, 2000:727-734.
  • 6KASS R E, WASSERMAN L. A reference Bayesian test for nested hy- pothesis and its relationship to the Schwarz criterion [J ]. Journal of the American Statistical Association, 1995,90(431 ):928-934.
  • 7ARORA S. Polynomial time approximation schemes for Euclidean TSP and other geometric problems [ C ]//Proc of the 37th Annual IEEE Symposium on Foundations of Computer Science. [ S. 1. ] :IEEE Com- puter Society, 1996 : 2-11.
  • 8Canadian Forest Service. Canadian national fire database:agency fire data[ EB/OL]. http ://cwfis. cfsl nrcan, gc. ca/en_CA/nfdb.
  • 9Wu M, Xu J, Tang X, et al. Top-k monitoring in wireless sensor networks[J]. IEEE Transactions on Knowledge and Data Engineering, 2007 19(6):962.
  • 10Bai X, Xuan D, Yun Z, et al. Complete optimal de- ployment patterns for ~ull-coverage and k-connectivi- ty (k~6) wireless sensor networksEC]. New York, USA: ACM, 2008.

引证文献5

二级引证文献14

四川大学学报（自然科学版）
2010年 第5期

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