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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/109058


    Title: A Routing Optimization Strategy for Wireless Sensor Networks Based on Improved Genetic Algorithm
    Authors: Yao, Guangshun;Dong, Zaixiu;Wen, Weiming;Ren, Qian
    Keywords: Wireless Sensor Network;Genetic Algorithm;Crossover;Mutation
    Date: 2016-06
    Issue Date: 2017-01-03
    Publisher: 淡江大學出版中心
    Abstract: In order to resolve the problem of generating invalid new individual when using genetic
    algorithm for routing optimization in wireless sensor networks (WSNs), an improved genetic
    algorithm (ROS_IGA) is put forward. By considering the position and neighbors of nodes in WSNs,
    ROS_IGA takes reasonable crossover and mutation operation to ensure compliance with the
    topological of actual WSNs and the demand of communication among nodes. Furthermore, ROS_IGA
    takes many factors, such as the residual energy of sensor nodes, distance and energy consumption
    between adjacent nodes, communication delay and relay hops, into consideration to select suitable
    routing. So ROS_IGA increases the speed of convergence and optimizes the performance of WSNs.
    Finally, a simulation experiment is carried out and the experimental results show that the improved
    algorithm in this study can effectively finds the best routing and decreases energy consuming and also
    increases the network life cycle.
    Relation: Journal of Applied Science and Engineering 19(2), pp.221228
    DOI: 10.6180/jase.2016.19.2.13
    Appears in Collections:[Journal of Applied Science and Engineering] v.19 n.1

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