Toward a Robust Multi-Objective Metaheuristic for Solving the Relay Node Placement Problem in Wireless Sensor Networks

Sensors

JuanA. Gómez-Pulido¹  JoséM. Lanza-Gutiérrez²  Broderick Crawford³  Ricardo Soto³  Nuria Caballé⁴ 

[1] Escuela Polítécnica, Universidad de Extremadura, 10003 Cáceres, Spain;Escuela Técnica Superior de Ingenieros Industriales, Centro de Electrónica Industrial, Universidad Politécnica de Madrid, 28006 Madrid, Spain;Escuela de Ingeniería Informática, Pontificia Universidad Católica de Valparaíso, 2362807 Valparaíso, Chile;Facultad de Farmacia, Campus Montepríncipe, Universidad CEU San Pablo, 28668 Madrid, Spain;

关键词: deployment;    energy cost;    metaheuristic;    multi-objective;    relay node;    reliability;    sensitivity;    wireless sensor network;   

DOI  :  10.3390/s19030677

来源: DOAJ

【 摘 要 】

During the last decade, Wireless sensor networks (WSNs) have attracted interest due to the excellent monitoring capabilities offered. However, WSNs present shortcomings, such as energy cost and reliability, which hinder real-world applications. As a solution, Relay Node (RN) deployment strategies could help to improve WSNs. This fact is known as the Relay Node Placement Problem (RNPP), which is an NP-hard optimization problem. This paper proposes to address two Multi-Objective (MO) formulations of the RNPP. The first one optimizes average energy cost and average sensitivity area. The second one optimizes the two previous objectives and network reliability. The authors propose to solve the two problems through a wide range of MO metaheuristics from the three main groups in the field: evolutionary algorithms, swarm intelligence algorithms, and trajectory algorithms. These algorithms are the Non-dominated Sorting Genetic Algorithm II (NSGA-II), Strength Pareto Evolutionary Algorithm 2 (SPEA2), Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), Multi-Objective Artificial Bee Colony (MO-ABC), Multi-Objective Firefly Algorithm (MO-FA), Multi-Objective Gravitational Search Algorithm (MO-GSA), and Multi-Objective Variable Neighbourhood Search Algorithm (MO-VNS). The results obtained are statistically analysed to determine if there is a robust metaheuristic to be recommended for solving the RNPP independently of the number of objectives.

【 授权许可】

Unknown