Distributed energy-efficient clustering routing protocol for wireless sensor networks using affinity propagation and fuzzy logic

Abstract

Organizing nodes into clusters and forwarding data to the base station (BS) in clustering routing protocols have been widely utilized to improve the energy efficiency, scalability and stability of wireless sensor networks. Making decisions on how many clusters are formed, which nodes are selected as cluster heads (CHs) and who become the relay nodes significantly impact the network performance. Therefore, a distributed clustering routing protocol combined affinity propagation (AP) with fuzzy logic called DAPFL is proposed in this paper, which considers not only energy efficiency but also energy balance to extend the network lifetime. In DAPFL, AP is firstly used to determine the number of clusters and select the best CHs simultaneously based on residual energy, distance between nodes. Then, the optimal next-hop CHs are chosen by using fuzzy logic system with residual energy, data length and distance to BS as descriptors. Simulations in different scenarios are carried out to verify the effectiveness of DAPFL, and the results show that DAPFL exhibits the promising performance in terms of network energy consumption, standard deviation of residual energy, network throughput and lifetime, compared with the up-to-date distributed clustering routing protocols EEFUC, EEFRP, LEACH-AP and APSA.