一种带有可控阈值参数的分簇路由优化算法

针对传感网中大量冗余数据导致通信频繁中断的问题,提出一种带有可控阈值参数的分簇路由优化算法。引入蚁群算法中的适应度函数和启发式函数,使得下一跳簇首节点的选择更具针对性,实现网络路由树的建立与事件域节点的分布式成簇。利用可控阈值参数和变异系数对网络路由所选最短路径进行优化,保证节点能量消耗较低的同时全网延时最小,并通过全局信息素的更新策略抑制长链路的产生,以均衡全网能量并延长网络生存周期。实验结果表明,该算法与DMOA和MTTA算法在抑制网络能量消耗和延长网络生存周期方面进行对比,其性能指标平均提升了13.72%和12.06%。

An Optimized Clustering Routing Algorithm with Controllable Threshold Parameter

To address frequent interrupts of communication networks caused by a large amount of redundant data in sensor networks.This paper proposes an optimized clustering routing algorithm with controllable threshold parameters.The algorithm introduces the fitness function and heuristic function in the ant colony algorithm to make the selection of the cluster head node of the next hop more targeted,and realize the establishment of the network routing tree and distributed clustering of the event domain nodes.Then the controllable threshold parameters and variation coefficient are used to optimize the shortest path selected by the network routing,so that the energy consumption of the nodes can be reduced,and network delay can be minimized.Finally the algorithm uses the update strategy of global pheromone to suppress the generation of long links,balance network energy,and extend network lifetime.Experimental results show that compared with DMOA and MTTA algorithms,this algorithm has improved 13.72%and 12.06%respectively in terms of suppressing network energy consumption and extending network lifetime.