Open AccessMaximising network lifetime and energy efficiency of wireless sensor network using group search Ant lion with Levy flight
Author(s) -
NavnathDattatraya Kale,
Rao K. Raghava
Publication year - 2020
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2018.5778
Subject(s) - computer science , cuckoo search , wireless sensor network , selection (genetic algorithm) , particle swarm optimization , genetic algorithm , efficient energy use , base station , ant colony optimization algorithms , energy consumption , ant colony , distributed computing , computer network , artificial intelligence , algorithm , engineering , machine learning , electrical engineering
Wireless sensor network (WSN) is one of the emerging techniques, providing pervasive computing for different implementations. Some of the renowned problems in WSN are energy consumption, as well as, the extension of network lifetime. Moreover, cluster head (CH) selection is one of the essential criteria since it has direct communication with the base station. Several researchers are in progress in designing the energy‐efficient model. However, the problems are not yet rectified completely, which leads to the poor performance of WSN. This study intends to maximise the lifetime of the WSN by introducing an efficient CH selection algorithm. The CH selection is a crucial step that aids in improving the energy efficiency and network lifetime of a WSN. This study proposes a hybrid optimisation process named group search ant lion with Levy flight for choosing the CH in WSN. The proposed model is compared to the conventional models such as genetic algorithm, particle swarm optimisation, artificial bee colony, group search optimisation, ant lion optimisation and cuckoo search. The outcome of the simulation result shows the superiority of the proposed model by prolonging the lifetime of the network.