Paper Info
Title
Studying the multiobjective variable neighbourhood search algorithm when solving the relay node placement problem in Wireless Sensor Networks
Abstract
Nowadays, wireless sensor networks (WSNs) are considered in many fields of application. In this paper, we study how to efficiently deploy relay nodes into previously established static WSNs, with the purpose of optimising two relevant factors for the industry: average energy consumption of the sensors and average sensitivity area provided by the network. This is the so-called relay node placement problem, which is a known NP-hard optimisation problem in the literature. With the purpose of tackling this multiobjective (MO) optimisation problem, we consider two different approaches of the trajectory algorithm MO-VNS, assuming a wide range of stop conditions. Two additional standard genetic algorithms are included in this study, NSGA-II and SPEA2, which belong to evolutionary algorithms. The aim is to analyse the behaviour of MO-VNS compared to traditional methodologies. To this end, the four metaheuristics are applied to solve a freely available data set. The results obtained are analysed following a widely accepted statistical methodology and considering three MO quality metrics: hypervolume, set coverage, and attainment surface. After studying the results, we conclude that MO-VNS provides better performance than the standard algorithms NSGA-II and SPEA2. Moreover, we verify that the addition of relay nodes is a good way to optimise traditional WSNs.
Year
DOI
Venue
2016
10.1007/s00500-015-1670-0
soft computing
Keywords
Field
DocType
Coverage, Energy efficiency, Metaheuristic, Multiobjective optimisation, Relay node, Wireless sensor network
Key distribution in wireless sensor networks,Mathematical optimization,Standard algorithms,Search algorithm,Evolutionary algorithm,Computer science,Artificial intelligence,Wireless sensor network,Relay,Machine learning,Genetic algorithm,Metaheuristic
Journal
Volume
Issue
ISSN
20
1
1433-7479
Citations 
PageRank 
References 
2
0.37
36
Authors
2
Name
Order
Citations
PageRank
José Manuel Lanza-Gutiérrez150.73
Juan Antonio Gómez Pulido2465.88