Title: A hybrid BFO-FOA-based energy efficient cluster head selection in energy harvesting wireless sensor network
Authors: Maddali M.V.M. Kumar; Aparna Chaparala
Addresses: Department of Computer Science and Engineering, Acharya Nagarjuna University, Guntur, Andhra Pradesh, India ' Department of Computer Science and Engineering, RVR&JC College of Engineering, Guntur, Andhra Pradesh, India
Abstract: This paper proposed a hybrid bacterial foraging optimisation (BFO) and fruitfly optimisation algorithm (FOA) for energy efficient cluster head (CH) selection in wireless sensor network. The bacterial foraging optimisation algorithm is inspired by the group foraging behaviour of bacteria such as E. coli and M. xanthus realising chemistry in the environment and moving away from specific signals. The FOA is simple framework and easy to implement for solving an optimisation problem with different characteristics. It is robust and fast algorithm and used to solve discrete optimisation problems. The performance metrics of the proposed method is evaluated for end to end delay, packet delivery, drop ratio, energy consumption, network lifetime and throughput. The simulation results show that the proposed method achieves better energy efficiency and network lifetime of 35%, 58%, and 67% compared to existing methods like ant colony optimisation, particle swarm optimisation and genetic algorithm.
Keywords: energy harvesting; wireless sensor network; WSN; energy efficiency; bacterial foraging optimisation; BFO; fruitfly optimisation algorithm; FOA; packet delivery ratio.
International Journal of Communication Networks and Distributed Systems, 2020 Vol.25 No.2, pp.205 - 222
Received: 05 Mar 2019
Accepted: 22 Apr 2019
Published online: 06 May 2020 *