Abstract: The limited energy of nodes in wireless sensor networks is prone to unbalanced energy load. To solve this problem, a routing algorithm for wireless sensor networks (WSN) is proposed based on the firefly algorithm to optimize fuzzy C-means (FCM). Both the clustering stage and the inter-cluster routing establishment stage in clustering routing algorithm are optimized in firefly algorithm to optimize fuzzy C-means (FFACM) algorithm. In the clustering stage, the firefly algorithm is used to calculate the initial clustering center, so as to avoid the problem that fuzzy C-means algorithm falls into local optimum due to the initial clustering center. To select the cluster head node, the fitness function about residual energy and distance is established, and the cluster head node with the largest fitness value is selected and dynamically updated. We calculate the link cost between nodes and establish the cost function according to the residual energy and the distance to the sink node, and then select the node with the smallest cost function value to establish the multi-hop routing between clusters, which minimizes the load of the cluster head node. The simulation results show that compared with other routing algorithms in wireless sensor networks, FFACM algorithm can effectively balance the network load, reduce the energy consumption of nodes, and thus it can prolong the network life cycle.

Key words: wireless sensor network, firefly algorithm, fuzzy C-means, link cost