Fuzzy based clustering and improved ant colony optimization for collecting data via mobile sink in wireless sensor networks

Abstract

Energy efficient routing of data from sensor to base station (BS) is attained utilizing the clustering of sensor nodes, thus minimizing the number of hops and circling the task of the cluster head (CH) sporadically. In addition, the clusters near to the BS take a substantial load over multi-hop communication. The hot spot problem affects wireless sensor networks (WSNs) with BS nodes, which is caused by sensor nodes close to the BS allowing for increased traffic load. So, the entire network lifespan is minimized owing to the element some nodes drain their energy resources much faster equated to the break. To solve these issues fuzzy based clustering and form the optimal route (FCOR) by mobile sink (MS) approach for efficient data collection is proposed. The fuzzy logic method is used for elected the CH by node remaining energy, node connectivity and node distance parameters. Discovering an optimal movable trajectory for the MS is serious so as to attain energy efficiency. Improved ant colony optimization (IACO) method is a better solution to discovering an optimal traversal route. Simulation results proves that FCOR increases the energy efficiency, throughput and minimized the network delay in the WSN.