Abstract: To overcome the deficiency of existing clustering algorithms of wireless sensor networks, a clustering routing algorithm based on improved genetic algorithm is proposed. First, to accelerate convergence and avoid local convergence of traditional genetic algorithm, an improved genetic algorithm based on harmony algorithm and adaptive optimization method is proposed. Then, the optimal number of cluster heads is derived using the network energy consumption model and node distribution model. Finally, the optimal cluster heads are selected using improved genetic algorithm. The energy of the node, the distance from the sink, the density of neighbor nodes and other factors are considered during the design of the fitness function. In order to balance and reduce energy consumption, the energy and location factors are considered when defining the clustering selection function and relay cost function. Simulation results show that the proposed algorithm can realize load balancing and  reduce network energy consumption effectively.

Key words: clustering routing algorithm, self-adaptive clustering, genetic algorithm, sensor network