FCWWO: Fuzzy Chaotic Whale Wolf Optimization for Enhancing Network Lifetime and Minimizing Energy Consumption

Abstract

Abstract The Wireless Sensor Networks (WSN) include several sensors which collect data from their surroundings and transmit it to the destination node. In WSN, sensor nodes operate individually and build the ad-hoc network infrastructure. The observing data perceives the sensor nodes and the data have been sent to the Base Station (BS) with the utilization of gateway and Cluster Head (CH). The WSNs have limited battery power which diminishes the lifetime of the network. The clustering algorithm is one of the efficient solutions that help in improving the WSNs network. Many algorithms were applied in the clustering process in rectifying the issue of NP-hard optimization. But, these algorithms lead to disadvantages namely delay, slow conveyance rate and weak exploitation stage. Therefore, in this paper, a novel Fuzzy Chaotic Whale Wolf (FCWW) optimization is proposed for selecting the optimal CH. The primary goal of our article is to lessen computational complexity with increased network lifetime. The main operation of the CH is gathering information from the sensor nodes and directly communicating with the BS. As compared to other techniques, the proposed FCWW algorithm provides 712 kbps of throughput, 98.8% of packet delivery ratio, network lifetime of 1652 seconds, 35% of energy consumption and 82 ms of end-to-end latency respectively.