Clustering routing algorithm for WSNs based on chaotic improved GWO
Aiming at the problem of unbalanced energy consumption and load of wireless sensor networks (WSNs),a clustering routing algorithm based on chaotic improved grey wolf optimization(CIGWO)is proposed. By chaotization of parameters of original GWO algorithm and adding chaotic mapping population in iteration,the strategy of grey population location update is improved and the global search ability of GWO algorithm is enhanced. According to the average residual energy of nodes fitness function is designed selected globally the optimal cluster head reduce the energy consumption of the network. Simulation results show that compared with LEACH,HEED and fittness improved GWO(FIGWO)algorithms,the proposed algorithm can effectively balance node load,reduce network energy consumption,and extend network life.
wireless sensor networksgrey wolf optimizationchaotic mappingenergy consumption balancecluster head selectionrouting algorithm
万方数据
维普
