期刊文献+

一种基于A-means聚类算法的Sweep Coverage机制 被引量:4

Sweep Coverage approach with A-means clustering algorithm
在线阅读 下载PDF
导出
摘要 为了改进Sweep Coverage机制在真实场景中的性能,提出了一种基于聚类的Sweep Coverage机制(cluste-ring-based sweep coverage,CBSC),该机制引入一种自适应的聚类算法A-means(self-adaptiveK-means algotithm)来控制节点的移动。实验结果表明,在真实的监控场景中,CBSC机制较以往的覆盖机制取得了更好的性能表现。 The key issue of sweep coverage scheme is to schedule the sensor' s mobility effectively in real scene. In this work, this paper proposed a novel Sweep Coverage approach with A-means (self-adaptive K-means algorithm) clustering algorithm named CBSC. The simulation results show that the CBSC achieves better performance than existing approaches in real scene.
出处 《计算机应用研究》 CSCD 北大核心 2012年第3期1051-1053,共3页 Application Research of Computers
基金 国家自然科学基金资助项目(60773168)
关键词 无线传感器网络 覆盖机制 扫描覆盖 移动控制 聚类 K-均值 wireless sensor networks(WSN) coverage scheme Sweep Coverage mobility control clustering K-means
  • 相关文献

参考文献9

  • 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.
  • 4王伟,林锋,周激流.Sweep Coverage中的节点移动控制[J].四川大学学报(自然科学版),2010,47(5):1015-1019. 被引量:5
  • 5JAIN A. Data clustering: 50 years beyond K-means [J]. Pattern Recognition Letters ,2010,31 ( 8 ) :651-666.
  • 6PELLEG 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.
  • 7KASS 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.
  • 8ARORA 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.
  • 9Canadian Forest Service. Canadian national fire database:agency fire data[ EB/OL]. http ://cwfis. cfsl nrcan, gc. ca/en_CA/nfdb.

二级参考文献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

共引文献4

同被引文献24

  • 1Cardei M, Wu J. Handbook of sensor networks[M]. Boca Raton: CRC Press, 2005.
  • 2Mulligan R, Ammari H M. Coverage in wireless sensor networks: a survey [J]. NPA, 2010, 2 (2) : 1943.
  • 3Bai X, Kumar S, Xuan D, et al. Deploying wire- less sensors to achieve both coverage and connec- tivity [C] //Proceeding of the 7th ACM interna- tional symposium on Mobile ad hoc networking and computing, Florence, 2006.New York: Associa- tion for Computing Machinery, 2006.
  • 4Bai X L, Xuan D, Yun Z Q, et al. Complete op- timal deployment patterns for full-coverage and k - connectivity (k < 6) wireless sensor networks [C] //Proceedings of the 9th ACM International Symposium on Mobile Ad hoc Networking and Computing. New York: ACM Press, 2008.
  • 5Kumar S, Lai T H, Arora A. Barrier coverage with wireless sensors [C] //Proceedings of the llth annual international conference on Mobile computing and networking, Cologne, 2005. New York: ACM Press, 2005.
  • 6Cheng W F, Li M, Liu K, et al. Sweep cover- age with mobile sensors [C] //Proceedings of IEEE International Symposium on Parallel and Dis- tributed Processing. Miami, Washington DC: IEEE Computer Society, 2008.
  • 7GuY Y, Bozdag D, Brewer R W, et al. Data har- vesting with mobile elements in wireless sensor networks [ J ] Comput Networks, 2006, 50 (17) : 3449.
  • 8Snydera L V, Daskin M S. A random-key genetic algorithm for the generalized traveling salesman problem [J]. EJOR, 2006, 174 (1): 38.
  • 9吴志远,邵惠鹤,吴新余.遗传退火进化算法[J].上海交通大学学报,1997,31(12):69-71. 被引量:46
  • 10王伟,林锋,周激流.Sweep Coverage中的节点移动控制[J].四川大学学报(自然科学版),2010,47(5):1015-1019. 被引量:5

引证文献4

二级引证文献9

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部