一种改进粒子群的无线传感网络能量优化模型设计

Energy optimization model for wireless sensor networks with improved particle swarm optimization

针对传统无线路由算法节点选择存在很大的随机性,一旦选择边沿节点将造成长距离通信,从而降低通信效率的问题,设计了一种基于改进粒子群算法的能量优化模型。该模型利用改进粒子群算法对簇头选择进行优化,并综合考虑簇头能量、簇头传输距离、簇头分布等因素,设计新的适应度函数,从而在大范围内降低网络传输的能量损耗。此外还针对无线网络节点过早死的问题,提出一种基于最小能耗的单级跳和多级跳结合的通信方式,从而均衡整个无线网络能量,延长整个网络的寿命。最后通过仿真验证了模型的可行性。

There is a lager random in traditional wireless routing algorithm for choosing nodes,and once selected edge nodes will cause long distance communication,thereby reduce the efficiency of communication. Aiming at above problem,it proposes an energy optimization model based on improved particle swarm optimization algorithm. Using the improved particle swarm algorithm,it optimizes the cluster head selection,and designs a new fitness function for energy of the cluster head cluster head,transmission distance,cluster head distribution and other factors into consideration. This method can reduce the maximum range of network transmission energy loss.In view of the wireless network node premature death,it puts forward a multi path communication mode based on minimum energy consumption,balances the entire wireless network energy and prolongs the network lifetime.The simulation proves this method.