期刊文献+

基于最优刚性图的链路质量与能量的拓扑控制算法 被引量:3

Link quality and energy topology control algorithm based on optimally rigid graph
原文传递
导出
摘要 针对目前无线传感器网络研究中网络能量利用率低和通信链路不可靠等问题,提出一种基于最优刚性图的网络拓扑优化算法.该算法通过建立包含链路质量和能量两方面内容的链路权值函数来构建链路可靠性强、能量利用率高的网络拓扑结构.研究结果表明,所构建的拓扑具有平均节点度低和链路性能好等优越特性.仿真结果表明,与现有拓扑控制算法相比,所提出的算法能够更有效地减少能量消耗,从而延长网络寿命. By noting the problem such as low energy efficiency and unreliable communication links in existing studies on wireless sensor networks(WSNs), a novel topology control algorithm based on the optimally rigid graph theory is proposed.A function, which can comprehensively reflect both link quality and energy consumption, is built to weight communication links with strong reliability and high efficient utilization of energy in the proposed algorithm. It is proved that the proposed algorithm has the properties of low average node degrees and good link performance. Finally, some simulation results show that the energy consumption can be reduced efficiently and network life can be prolonged by using the proposed algorithms,compared with the existing topology control algorithms.
出处 《控制与决策》 EI CSCD 北大核心 2015年第11期2055-2060,共6页 Control and Decision
基金 国家973计划项目(2010CB731800) 国家自然科学基金项目(61074065 61375105) 河北省自然科学基金项目(F2012203119)
关键词 无线传感器网络 拓扑优化 最优刚性图 链路质量 能量消耗 wireless sensor network topology optimization optimally rigid graph link quality energy loss
  • 相关文献

参考文献4

二级参考文献35

  • 1卿利,朱清新,王明文.异构传感器网络的分布式能量有效成簇算法[J].软件学报,2006,17(3):481-489. 被引量:159
  • 2李成法,陈贵海,叶懋,吴杰.一种基于非均匀分簇的无线传感器网络路由协议[J].计算机学报,2007,30(1):27-36. 被引量:371
  • 3刘刚,李志刚,朱兴国,周兴社.DCPC:基于能量保护的传感器网络分布式拓扑控制协议[J].计算机科学,2007,34(4):28-31. 被引量:1
  • 4Heinzelman W, Chandrakasan A, Balakrishnan H. Energy- efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd Annual Hawaii International Conference on System Sciences. Maui, USA: IEEE, 2000. 1-10.
  • 5Heinzelman W, Chandrakasan A, Balakrishnan H. An applicatiomspecific protocol architecture for wireless micro sensor networks. IEEE Transactions on Wireless Communications, 2002, 1(4): 660-670.
  • 6Lindsey S, Raghavendra C, Sivalingam K M. Data gathering algorithms in sensor networks using energy metrics. IEEE Transactions on Parallel and Distributed Systems, 2002, 13(9): 924-935.
  • 7Dasgupta K, Kalpakis K, Namjoshi P. An efficient clustering-based heuristic for data gathering and aggregation in sensor networks. In: Proceedings of the IEEE Conference on Wireless Communications and Networking. New Orleans, USA: IEEE, 2003. 1948-1953.
  • 8Choi W, Shah P, Das S K. A framework for energy-saving data gathering using two-phase clustering in wireless sensor networks. In: Proceedings of the International Conference on Mobile and Ubiquitous Systems: Networking and Services. Boston, USA: IEEE, 2004. 203-212.
  • 9Oberg L, Xu Y Z. A complete energy dissipation model for wireless sensor networks, sensorcomm. In: Proceedings of the International Conference on Sensor Technologies and Applications. Valencia, Spain: IEEE, 2007. 531-540.
  • 10Niculcscu D, Nath B. Localized positioning in ad hoc net- works. Journal of Ad Hoc Networks, Special Issue on Sen- sor Network Protocols and Applications, 2003, 1(2-3): 211-349.

共引文献19

同被引文献22

引证文献3

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