Node Placement Optimization of Wireless Sensor Networks Using Multi-Objective Adaptive Degressive Ary Number Encoded Genetic Algorithm

The wireless sensor network (WSN) has the advantages of low cost, high monitoring accuracy, good fault tolerance, remote monitoring and convenient maintenance. It has been widely used in various fields. In the WSN, the placement of node sensors has a great impact on its coverage, energy consumption...

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Veröffentlicht in:Algorithms Jg. 13; H. 8; S. 189
Hauptverfasser: Zhang, Yijie, Liu, Mandan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 01.08.2020
Schlagworte:
a fast non-dominated sorted genetic algorithm (NSGA2)
adaptive
Adaptive algorithms
Connectivity
degressive ary number
Energy consumption
Fault tolerance
Genetic algorithms
Linear programming
Multiple objective analysis
node placement
Nodes
Objectives
Optimization
Optimization algorithms
Placement
Remote monitoring
Sensors
Wireless networks
Wireless sensor networks
ISSN:1999-4893, 1999-4893
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Zusammenfassung:The wireless sensor network (WSN) has the advantages of low cost, high monitoring accuracy, good fault tolerance, remote monitoring and convenient maintenance. It has been widely used in various fields. In the WSN, the placement of node sensors has a great impact on its coverage, energy consumption and some other factors. In order to improve the convergence speed of a node placement optimization algorithm, the encoding method is improved in this paper. The degressive ary number encoding is further extended to a multi-objective optimization problem. Furthermore, the adaptive changing rule of ary number is proposed by analyzing the experimental results of the N-ary number encoded algorithm. Then a multi-objective optimization algorithm adopting the adaptive degressive ary number encoding method has been used in optimizing the node placement in WSN. The experiments show that the proposed adaptive degressive ary number encoded algorithm can improve both the optimization effect and search efficiency when solving the node placement problem.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1999-4893
1999-4893
DOI:10.3390/a13080189