计算机应用 ›› 2011, Vol. 31 ›› Issue (11): 2898-2901.DOI: 10.3724/SP.J.1087.2011.02898

• 网络与通信 • 上一篇    下一篇

基于蚁群的无线传感网最大化生存时间路由

陈友荣1,2,俞立1,董齐芬1,洪榛1   

  1. 1. 浙江工业大学 信息工程学院,杭州 310032
    2. 浙江树人大学 信息科技学院,杭州 310015
  • 收稿日期:2011-05-10 修回日期:2011-07-04 发布日期:2011-11-16 出版日期:2011-11-01
  • 通讯作者: 陈友荣
  • 作者简介:

    陈友荣(1982-),男,浙江苍南人,讲师,博士研究生,主要研究方向:无线传感器网络、车载网络;
    俞立(1961-),男,浙江富阳人,教授,博士生导师,主要研究方向:鲁棒控制、网络控制;
    董齐芬(1985-),女,浙江富阳人,博士研究生,主要研究方向:无线传感器网络;

    洪榛(1984-),男,浙江台州人,博士研究生,主要研究方向:无线传感器网络。

  • 基金资助:
    浙江省教育厅资助项目;浙江树人大学校资助项目

Maximum lifetime routing based on ant colony in wireless sensor network

CHEN You-rong1,2,YU Li1,DONG Qi-fen1,HONG Zhen1   

  1. 1. College of Information Engineering, Zhejiang University of Technology, Hangzhou Zhejiang 310032, China
    2. College of Information Science and Technology, Zhejiang Shuren University, Hangzhou Zhejiang 310015, China
  • Received:2011-05-10 Revised:2011-07-04 Online:2011-11-16 Published:2011-11-01
  • Contact: CHEN You-rong

摘要: 为提高无线传感网的生存时间,对基于蚁群算法的最大化生存时间路由(MLRAC)进行了研究。该路由利用链路能耗模型和节点发送数据概率,计算一个数据收集周期内节点总能耗。同时考虑节点初始能量,建立了最大化生存时间路由的最优模型。为求解该最优模型,在经典蚁群算法的基础上,提出修正的蚁群算法。该算法采用新的邻居节点转发概率公式、信息素更新公式和分组探测方法,经过一定的迭代计算获得网络生存时间的最优值和每个节点的最优发送数据概率。最后,Sink节点洪泛通知网络中所有节点。节点根据接收到的最优概率,选择数据分组未经过的邻居节点发送数据。仿真实验表明,经过一定时间的迭代,MLRAC的生存时间可以收敛到最优值。该算法能延长网络生存时间,在一定的条件下,MLRAC算法比PEDAP、LET、Ratio-w、Sum-w等算法更优。

关键词: 无线传感网, 蚁群算法, 网络生存时间, 路由

Abstract: To prolong the lifetime in wireless sensor networks, the maximum lifetime routing based on ant colony algorithm (MLRAC) was proposed. This paper used the link energy consumption model and node transmission data probability to calculate the node total energy consumption in a data gathering cycle. Considering the node initial energy, MLRAC formulized the maximum lifetime routing into an optimal model. To solve the optimal model, the revised ant colony algorithm based on classical algorithm was proposed. It used new formulas for forwarding the probability of neighbor nodes and pheromone update, and a new method for packet detection. After some iterations of calculation, it could obtain the optimal network lifetime value and each node transmission data probability. Finally, sink node informed any other nodes in network with flooding. According to the received optimal probability, all nodes selected the neighbor node where the data packets did not pass to transmit data. The simulation results show that after a certain time of iteration, network lifetime of MLRAC reaches certain convergence. It can prolong network lifetime. Under certain conditions, MLRAC outperforms PEDAP-PA, LET, Sum-w and Ratio-w algorithms.

Key words: Wireless Sensor Network (WSN), Ant Colony Algorithm (ACA), network lifetime, routing

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