An Improved Niche Chaotic Genetic Algorithm for Low-Energy Clustering Problem in Large-Scale Wireless Sensor Networks
Joint Authors
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-04-01
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Large-scale wireless sensor networks consist of a large number of tiny sensors that have sensing, computation, wireless communication, and free-infrastructure abilities.
The low-energy clustering scheme is usually designed for large-scale wireless sensor networks to improve the communication energy efficiency.
However, the low-energy clustering problem can be formulated as a nonlinear mixed integer combinatorial optimization problem.
In this paper, we propose a low-energy clustering approach based on improved niche chaotic genetic algorithm (INCGA) for minimizing the communication energy consumption.
We formulate our objective function to minimize the communication energy consumption under multiple constraints.
Although suboptimal for LSWSN systems, simulation results show that the proposed INCGA algorithm allows to reduce the communication energy consumption with lower complexity compared to the QEA (quantum evolutionary algorithm) and PSO (particle swarm optimization) approaches.
American Psychological Association (APA)
Tian, Min& Zhou, Jie& Lv, Xin. 2018. An Improved Niche Chaotic Genetic Algorithm for Low-Energy Clustering Problem in Large-Scale Wireless Sensor Networks. Journal of Sensors،Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1201499
Modern Language Association (MLA)
Tian, Min…[et al.]. An Improved Niche Chaotic Genetic Algorithm for Low-Energy Clustering Problem in Large-Scale Wireless Sensor Networks. Journal of Sensors No. 2018 (2018), pp.1-8.
https://search.emarefa.net/detail/BIM-1201499
American Medical Association (AMA)
Tian, Min& Zhou, Jie& Lv, Xin. An Improved Niche Chaotic Genetic Algorithm for Low-Energy Clustering Problem in Large-Scale Wireless Sensor Networks. Journal of Sensors. 2018. Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1201499
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1201499