一种基于蚁群算法优化的WSN分簇路由算法

为了实现无线传感器网络对节点能量的高效利用,提出了一种蚁群优化的分簇路由算法CRAACA。该算法引入簇内平均剩余能量参数,对簇首选择阈值进行改进,以均衡簇内能耗;根据节点间的位置关系建立节点的可中继节点集,控制蚁群算法的搜索空间;蚁群在对可中继节点集进行路径搜索时考虑节点间的距离和节点的剩余能量,以生成节能和较好均衡网络能耗的多跳网络路由;对生成的多径路由依相应概率选择数据传输的路径,提高数据传输的可靠性。仿真结果表明,该算法在网络能量的利用效率、数据传送成功率,以及延长网络生存周期等方面具有较好的性能。

An Optimized Clustering Routing Algorithm for Wireless Sensor Network Based on Ant Colony Algorithm

In order to improve the nodes’ energy efficiency of w ireless sensor networks (WSN), an optimized clustering routing algorithm based on ant colony algorithm (CRA-ACA) is proposed. The CRA-ACA is established according to the position relationships between nodes to construct a relay node set so that the searching space of ant colony algorithm can be optimized. Considering the residual energy of nodes and the distance between them during the path searching of ACA, a multi-hop network with balanced energy consumption is established. The routes of data transmission can be selected by probability so that the reliability of data transmission is improved. The CRA-ACA is also evaluated by simulation. The results indicate that the CRA-ACA has better performance in terms of energy efficiency, reliability of data transmission, and WSN lifespan.