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一种改进的蚁群WSN路由算法 被引量:2

An Improved Ant Colony Competition Routing Algorithm for WSN
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摘要 针对能量控制和拥塞控制在无线传感器网络路由上的特殊要求,利用蚁群算法(Ant Colony System,ACS)对路由中最短路径加速收敛。为了促使网络节点能量消耗相对均衡,提出一种改进的蚁群路由算法。该算法将多蚁群挥发的信息素与网络节点剩余能量结合成算法控制因子,并且引入了多蚁群竞争机制来避免单一收敛。此算法能有效地控制网络拥塞,并使网络节点能量消耗相对均衡,延长了整个网络的生命周期,实现了高效路由与能量消耗的较优权衡。最后通过Matlab仿真实验验证了该方法的可行性,并给出实验结果。 Aiming at special demand of energy control and congestion control on wirless sensor notwork route, Ant Colony System(ACS)is used to accelerate convergence of shortest range. A kind of improved ACS is proposed to balance network node consume. The pheromone and the energy of the node are combined to affect the pheromone concentration in optimization path, which can avoid network congestion and fast consume of energy of individual node. Then it can prolong the lifecycle of the whole network. The feasibility of this algorithm has been validated,and the results of experiment have been presented.
出处 《现代电子技术》 2007年第22期23-26,共4页 Modern Electronics Technique
关键词 蚁群算法 生命周期 能量路由 信息素 ant colony system life cycle energy routing pheromone
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参考文献10

  • 1Rajagopalan S,Jaikaeo C,Shen C C.Unicast Routing for Mobile Ad hoc Networks with Swarm Intelligence[EB/OL].http://www.cis.ude l.edu/~ rajagopa/ ansi-unicast-udcistr-2003-07 -dt:05-01-2003.pdf,2004.10.
  • 2Xu Y,Heidemann J,Estrin D.Geography-informed Energy Conservation for Ad Hoc Routing[A].Proc.7th Ann.Int.Conf.on Mobile Computing and Networking[C].2001:70-84.
  • 3Heinzelman W R,Chandrakasan A,Balakrishnan H.Energy Efficient Communication Protocol for Wireless Micro Sensor Networks[A].Proc Hawaii Int Conf on System Sciences[C].Hawaii,2000:3 005-3 014.
  • 4John S Baras,Harsh Mehta.A Probabilistic Emergent Routing Algorithm form Mobile Ad Hoc Networks[A].In Wiopt'03:Modeling and Optimization in Mobile,Ad Hoc and Wire less Networks,Sophia-Antipolice[C].France,2003:120-125.
  • 5Mesut Gunes,Udo Sorges,Imed Bouazizi.ARA-The Ant Colony-based Routing Algorithm for MANETs[A].In Inter-national Conference on Parallel Processing Workshops (ICPPW 02)[C].Vancouver B C,Canada,2002:79-85.
  • 6Heissenb Uttel M,Braun T.Ants-based Routing in Large Scale Mobile Ad-Hoc Networks[A].In Proceedings of the 13th ITG/GI-Fachtagung Kommunikation inverteilten System (KiVS 2003)[C].Leipzig,Germany,2003:181-190.
  • 7Hussein O,Saadawi T.Ant Routing Algorithm for Mobile Ad-Hoc Networks (ARAMA)[A].In Proc.of the 2003 IEEE International Conference on Performance,Computing,and Communications Conference[C].Phoenix,Arezone,2003:281-290.
  • 8Schoonderwoerd R,Holland O,Bruten J,et al.Ant-based Load Balancing in Telecommunications Networks[J].Adaptive Behavior,1996,5 (2):169-207.
  • 9Yongcai Wang,Zhao Q,Zheng D.Energy-driven Adaptive Clustering Data Collection Protocol in Wireless Sensor Networks[A].Proc.Int.Conf.on Information Mecatronics and Automation[C].Chengdu,2004:599-604.
  • 10Shnayder V,Hempstead M,Chen B.Simulating the Power Consumption of Large-scale Sensor Network Applications[A].Proc of SENSYS'04[C].Baltimore,2004:188-200.

同被引文献14

  • 1张静乐,王世卿,王乐.具有新型遗传特征的蚁群算法[J].微计算机信息,2006,22(02Z):261-263. 被引量:28
  • 2汪泉弟,李彬,刘青松.无线传感器网络能量多路径路由研究[J].信息与控制,2006,35(2):129-134. 被引量:13
  • 3梁华为,陈万明,李帅,梅涛,孟庆虎.基于蚁群优化的无线传感器网络能量均衡路由算法[J].模式识别与人工智能,2007,20(2):275-280. 被引量:12
  • 4Marco Dorigo,Vittorio Maniezzo, Alberto Colorni. Ant System:Optimization by a Colony of Cooperating Agents. IEEE Transactions on System, Man and Cybernetics Part B: Cybernetics,1996,26(1):29-41.
  • 5Davis L,The Handbook of Genetic Algorithms[M]. NewYork, Van Nostrand Reing Old. 1991.
  • 6Colorn A, Dorigo M, Maniezzo V. Distributed Optimation by Ant Colonies[J]. In: Proc 1st Euopean Conf. Artificial Life. Pans, France: Elsevier, 1991 : 134 - 142.
  • 7Colorni A,Dorigo M,Maniezzo V,et al. Ant System for Job -Shop Scheduling [J]. Belgian Journal of Operations Research and Statistic Computing Science, 1994,34 ( 1 ): 39 -53.
  • 8Dorigo M, Gambardella L M. Ant Colony System: A Cooperative Learning Approach to the Travelling Salesman Problem[J]. IEEE Transactions on Evolutionary Computation, 1997,1(1):53 -66.
  • 9Stutzle T, Hoos H. The MAX - MIN Ant System and Local Search for the Travelling Salesman Problem[J]. Proceedings of IEEE-IECE-EPS'97, IEEE International Conference on Evolutionary Computation and Evolutionary Programming Conference, 1997:309 - 314.
  • 10Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E. Wire- less sensor networks: A survey. Computer Networks , 2002,38 (4): 393-422.

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