Open AccessFitness function improvement of evolutionary algorithms used in sensor network optimisations
Author(s) -
Hoseinpour Atiieh,
Lahijani Mojtaba Jafari,
Hoseinpour Mohammad,
Kazemitabar Javad
Publication year - 2018
Publication title -
iet networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.466
H-Index - 21
ISSN - 2047-4962
DOI - 10.1049/iet-net.2017.0251
Subject(s) - fitness function , wireless sensor network , evolutionary algorithm , computer science , software deployment , function (biology) , core (optical fiber) , energy consumption , algorithm , artificial intelligence , machine learning , genetic algorithm , engineering , computer network , telecommunications , evolutionary biology , electrical engineering , biology , operating system
Recent advances in wireless sensor network (WSN) technology are enabling the deployment of large‐scale and collaborative sensor networks. WSNs face several challenges such as security, localisation, and energy consumption. To resolve these issues, evolutionary algorithms can be helpful. The core of every evolutionary algorithm is its fitness function. The drawbacks of fitness functions used in the literature will be investigated and some solutions will be suggested. The simulation results clearly show the improvement due to suggested solutions.