Fitness function improvement of evolutionary algorithms used in sensor network optimisations. Issue 3 (1st May 2018)

• Record Type: Journal Article
• Authors: Hoseinpour, Atiieh; Lahijani, Mojtaba Jafari; Hoseinpour, Mohammad; Kazemitabar, Javad
• Is Part Of: IET networks. Volume 7:Issue 3(2018)
• Page Start: 91
• Page End: 94
• Publication Date: 2018-05-01
• Subjects: wireless sensor networks -- evolutionary computation -- energy consumption; fitness function improvement -- evolutionary algorithms -- sensor network optimisations -- wireless sensor network technology -- large‐scale sensor networks -- collaborative sensor networks -- energy consumption; Computer network architectures -- Periodicals; Computer network protocols -- Periodicals; Information networks -- Periodicals; Telecommunication systems -- Periodicals; 004.605
• DOI: 10.1049/iet-net.2017.0251
• Languages: English
• ISSNs: 2047-4954

Abstract

Abstract : 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.