能耗均衡的多跳多路径认知分层路由算法

An energy-balanced multi-hop multi-path cognitive hierarchical routing algorithm

为了缓解频谱资源紧缺的现状,提高认知无线传感器网络能量消耗的均衡性,并减少网络的能量消耗,提出了一种适用于异构认知无线传感器网络的能耗均衡多跳多路径认知分层路由EMMCH算法。首先,根据节点剩余能量、节点位置和邻居节点密度改进了簇首选举概率;其次,结合竞争半径的概念,平衡区域簇首能耗;然后,根据节点信道可用性和剩余能量选举最优簇首,簇首总数依据动态选举的思想确定;最后,簇首节点选取剩余能量高、距离汇聚节点近且存在空闲信道的节点进行多跳传输路径规划,再结合沿途消耗和不均衡程度选取最优路径。仿真结果显示,与对比算法相比,EMMCH算法具有更长的生命周期、更高的稳定性、更多的数据传输量和更均衡的网络能耗。

In order to alleviate the current shortage of spectrum resources,the energy consumption balance of the cognitive wireless sensor network is improved,and the energy consumption of the network is reduced.An energy-balanced multi-hop multi-path cognitive hierarchical(EMMCH)protocol is proposed,which is suitable for heterogeneous cognitive wireless sensor networks.Firstly,the cluster head election probability is improved based on the remaining energy of the node,the location of the node,and the density of the neighbor nodes.Secondly,the concept of the competition radius is used to balance the energy consumption of the cluster heads.Then,the optimal cluster head is selected based on the channel availability and the remaining energy The number of cluster heads changes dynamically.Finally,the cluster head node selects the node with high residual energy,close to the convergent node,and an idle channel for multi-hop transmission path planning,and then selects the optimal path in combination with the consumption along the way and the degree of imbalance.Simulation results show that the EMMCH algorithm has a relatively longer life cycle,higher stability,more data transmission volume,and more balanced network energy consumption.