The wireless sensor network is of great interest due to its special features and applications. Due to the computational limitation and power supply of these networks, hierarchical cluster routing is mentioned as a solution to improve the problem of energy consumption and network lifetime. In our study, a fuzzy-based clustering routing protocol was proposed that uses network zoning and node residual energy parameters, node distance to the center of each zone, and node-to-base station angle as fuzzy input for cluster head selection. In the proposed method with the aim of reducing network energy consumption, the responsibility of choosing CHs in each area, determining the area of each node, calculating the distance of each node to the center and calculating the angle of each node was assigned to the BS. The proposed method was carried out with Farahzadi, LEACH, MSCR protocols in terms of network lifetime evaluation criteria, stability period, selection and number of CH and average residual energy in MATLAB environment. The comparison of the results showed that the proposed method has performed better in terms of criteria, so that the network lifetime as one of the important indicators, the proposed method has improved by 50%, 40% and 20%, respectively, compared to LEACH, Farahzadi and MSCR methods.

Wireless sensor networks (WSNs) built for multiple purposes consist of a number of sensor nodes and base station (BS). In designing these networks, hierarchical cluster routing protocol is used as a common solution for the challenge of energy consumption and longer network lifetime. The strategy of proposed method (FBCR) is basead on zoning and a fuzzy-based cluster routing protocol. In this method, some of the nodes are selected as cluster heads (CHs) that are responsible for sending data to the BS. For fuzzy input in CH selection, the criteria were used, including “residual energy of the node”, “node distance to the center of each region”, and “node angle to the BS”. Fuzzy logic was used as an algorithm for modeling decision-making and human experiences, to maintain energy balance and better CH selection. In FBCR, with the aim of reducing network energy consumption, the responsibility of selecting CHs in each region, determining the region of nodes, calculating distance from each node to the center, and calculating angle of nodes were assigned to the BS. FBCR is improved in terms of network lifetime, stability Period, selection and number of CHs, and the mean residual energy compared to Farahzadi, LEACH and MSCR methods.