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改进的蚁群优化算法在无线传感器网络中的应用 被引量:6

Improved ant-based routing algorithm for wireless sensor networks
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摘要 针对无线传感器网络节点能量十分有限的特点,将蚁群优化算法应用到传感器网络的路由中,提出了一种改进的蚁群路由算法(IARA)。在考虑节点剩余能量、传输方向和节点距离等因素的基础上,对基本蚁群算法的概率选择公式和信息素更新公式进行了改进,实现了能量在整个传感器网络上的均衡消耗。仿真结果表明:该算法减少了传感器网络的能量消耗,并且使能量消耗更加均衡,从而提高了整个无线传感器网络的生存寿命。 针对无线传感器网络节点能量十分有限的特点,将蚁群优化算法应用到传感器网络的路由中,提出了一种改进的蚁群路由算法(IARA)。在考虑节点剩余能量、传输方向和节点距离等因素的基础上,对基本蚁群算法的概率选择公式和信息素更新公式进行了改进,实现了能量在整个传感器网络上的均衡消耗。仿真结果表明:该算法减少了传感器网络的能量消耗,并且使能量消耗更加均衡,从而提高了整个无线传感器网络的生存寿命。
出处 《吉林大学学报(工学版)》 EI CAS CSCD 北大核心 2011年第S1期215-219,共5页 Journal of Jilin University:Engineering and Technology Edition
基金 上海市科委基础研究重点项目(10JC1405800) 上海市科委项目(08DZ1200505) 闵行区科委项目(2010MH181) 上海市教委重点学科(J51901) 上海电机学院项目(09C401)
关键词 计算机软件 无线传感器网络 蚁群算法 能量 computer software wireless sensor network ant colony algorithm energy
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参考文献10

  • 1梁华为,陈万明,李帅,梅涛,孟庆虎.一种无线传感器网络蚁群优化路由算法[J].传感技术学报,2007,20(11):2450-2455. 被引量:32
  • 2Akyildiz IF,Su W,Sankarasubramaniam Y,et al.A survey on sensor networks. IEEE Communications Magazine . 2002
  • 3Heinzelman WR,Chandrakasan A,Balakrishnan H.Energy-efficient communication protocol for wireless microsensor networks. Proceedings of the 33rd Annual Hawaii International Conference on System Sciences . 2000
  • 4Dorigo M,Gambardella LM.Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation . 1997
  • 5Chalermek Intanagonwiwat,Ramesh Govindan,Deborah Estrin,et al.Directed diffusion for wireless sensor networking. IEEE ACM Transactions on Networking . 2003
  • 6Heinzelman WB,Chandrakasan AP,Balakrishnan H.An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications . 2002
  • 7Stutzle T,Hoos H H.The MAX-MIN ant system and local search for the traveling salesman problem. Proceedings of the IEEE International Conference on Evolutionary Computation(ICEC’ 97) . 1997
  • 8Kwang Mong Sim,Weng Hong Sun.Multiple Ant-Colony Optimization for Network Routing. First International Symposium on Cyber Worlds(CW’02) . 2002
  • 9I KASSABALDIS,MA EI-Sharkawi,J MARKS R.Swarm intelligence for routing in communication networks. Global Telecommunications . 2001
  • 10Reza GhasemAghaei,ASM Mahfujur Rahman,Abdur Rahman, etc.Ant colony-based many-to-one sensory data routing in Wireless Sensor Networks. IEEE/ACS International Conference on Computer Systems and Applications . 2008

二级参考文献15

  • 1[1]Akyildiz I F,Su W,Sankarasubramanian Y,Cayirci E,A Survey on Sensor Networks[J].IEEE Communications Magazine,2002,40(8):102-114.
  • 2[2]Akkaya K,Younis M,A Survey on Routing Protocols for Wireless Sensor Networks[J],Ad Hoc Networks.2005,3(3):325-349.
  • 3[4]Intanagonwiwat C,Govindan R and Estrin D,Directed Diffusion:A Scalable and Robust Communication Paradigm for Sensor Networks[C]// The Proceedings of the 6th Annual ACM/IEEE International Conference on Mobile Computing and Networking (MobiCom'00),Boston,MA,August 2000.
  • 4[5]Bonabeau E,Dorigo M,and Theraulaz G,Inspiration for Optimization from Social Insect Behavior[J],Nature,July 2000,406:39-42.
  • 5[6]Dorigo M,and Gambardella L M,Ant Colony System:a Cooperative Learning Approach to the Traveling Salesman Problem[J],IEEE Transactions on Evolutionary Computation,1997,1(1),53-66.
  • 6[7]Bullnheimer B,Hart1 R F and Strauss C,Applying the Ant System to the Vehicle Routing problem[C]// The 2nd Metaheuristic Intemational Conference,Sophia-Antipolis,France (1997).
  • 7[8]Sim K M,Sun W H,Ant Colony Optimization for Routing and Load-Balancing:Survey and New Directions[J],IEEE Transactions on Systems,Man,and Cybernetics,Part A 33(5):560-572 (2003).
  • 8[9]Gutjahr W J,A Generalized Convergence Result for the Graph-Based ant System Methaheuristic[R],Manuscript,University of Vienna,2000.
  • 9[10]Gutjahr W J,A Graph-Based Ant System and Its Convergence[J],Future Generation Computer Systems,2000,16(8):873-888.
  • 10[11]Gutjahr W J,ACO Algorithms with Guaranteed Convergence to the Optimal Solution[R],Technical Report,University of Vienna,ISDS 2001-02.

共引文献31

同被引文献47

引证文献6

二级引证文献21

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