自适应人工免疫网络算法的无线传感网络拓扑结构优化

无线传感器网络(MWSN)具有动态拓扑的特性,因而节点移动、能量消耗等影响因素会导致传感器网络的寿命。在现有层次型拓扑控制算法的基础上,借鉴adhoc网络层次拓扑生成算法WCA的设计原理,提出一种应用于无线传感器网络的新型层次型拓扑结构优化算法。该算法综合考虑节点的能量和位置状况,为每个节点定义不同的权值,从中选出性能优越的节点担任簇首,同时通过设置节点度参数来确保最优的拓扑结构。同时依托自适应人工免疫网络算法,用于实现MWSNs的目标。仿真结果表明,改进的人工免疫网络算法(KC-AAINA)有助于找到良好的聚类配置和簇头数量,限制了节点能耗,改善了MWSN的网络寿命、能量消耗和分组传输,从而提高网络生命周期。

Topology optimization of wireless sensor networks relying on adaptive artificial immune network algorithm

The wireless sensor network(MWSN) has the characteristics of dynamic topology, so the influence factors such as node movement and energy consumption will lead to the life of the sensor network. Based on the existing hierarchical topology control algorithm, a new hierarchical topology optimization algorithm for wireless sensor networks is proposed by using the design principle of adcoc network hierarchy topology generation algorithm WCA. The algorithm considers the energy and position of the node comprehensively, defines different weights for each node, selects the nodes with superior performance as the cluster head, and ensures the optimal topology by setting the node degree parameters. At the same time, relying on adaptive artificial immune network algorithm to achieve the goal of MWSNs. The simulation results show that the improved artificial immune network algorithm(KC-AAINA) helps to find a good cluster configuration and cluster head number, limits node energy consumption, improves MWSN network lifetime, energy consumption and packet transmission, thereby improving Network life cycle.