无线传感器网络分簇算法的仿真研究  

Wireless Sensor Networks Simulation Study on Clustering Algorithms

作　　者：李会[1] 刘剑虹[2] 何鹏[1] 

机构地区：[1]齐齐哈尔大学通信与电子工程学院,黑龙江齐齐哈尔161006 [2]齐齐哈尔大学化工学院,黑龙江齐齐哈尔161006

出　　处：《计算机仿真》2011年第5期122-125,245,共5页Computer Simulation

基　　金：黑龙江省自然科学基金(E200935);黑龙江省教育厅科学研究项目(11541399)

摘　　要：针对无线传感器网络分簇中节点负载不均衡的问题,提出了一种基于免疫记忆粒子群优化算法的分簇算法。算法对能力异构环境下的无线传感器网络的适应性和扩展性较好,且节能高效,实现简单。该算法在每轮运算过程中,利用节点负载能力预评估因子和节点能量预评估因子对无线传感器网络进行区域分割,获得能量均衡及负载能力均衡的分区,并在分区中通过免疫记忆粒子群算法选取簇头,使簇头具有高能量、负载能力强的优点。仿真结果表明,算法不仅在能量有效性、负载均衡性方面有良好的效果,而且延长网络生命周期和缩短建簇时间。因此,该算法在解决无线传感器网络节点不均衡问题上具有一定的实用性。In view of the load balance problem during network clustering for wireless sensor network,a clustering algorithm based on immune memory particle swarm optimization is proposed.In the energy-heterogeneous network environments,the algorithm has better adaptability,scalability and energy efficient for wireless sensor networks,and is easy to realize.The algorithm segmentes the wireless sensor networks based on node residual energy and node spacing,obtaines appropriate partitions,and selects the cluster head in the partitions by the immune memory particle swarm to make sure that the cluster head has high energy.Simulation results show that the algorithm has good results in energy efficiency and load balance,and extends the network life and shortens the construction of cluster time.Therefore,the algorithm in wireless sensor networks has some relevance for solving the imbalance issue.

关 键 词：无线传感网络 分簇算法 免役记忆粒子群优化 负载均衡 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]