
Node deployment in wireless sensor networks using the new multi‐objective Levy flight bee algorithm
Author(s) -
Hajizadeh Nahid,
Javidan Reza,
Shamsinejad Pirooz,
Akbari Reza
Publication year - 2020
Publication title -
iet wireless sensor systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.433
H-Index - 27
eISSN - 2043-6394
pISSN - 2043-6386
DOI - 10.1049/iet-wss.2019.0083
Subject(s) - software deployment , wireless sensor network , computer science , scale (ratio) , algorithm , node (physics) , metaheuristic , distributed computing , mathematical optimization , computer network , engineering , mathematics , physics , quantum mechanics , operating system , structural engineering
Wireless sensor networks (WSNs) play a prominent role in the world of computer networks. WSNs rely on deployment as a basic requirement and an effective factor on the basic network services. In deployment, creating a balance between conflicting optimisation factors, e.g. connectivity and coverage, is a challenging and sophisticated issue, so that deployment turns into an NP‐complete problem. The majority of existing researches has attempted to tackle this problem by applying classic single‐objective metaheuristic algorithms in 2D small‐scale uniform environments. In this study, a new hybrid multi‐objective optimisation algorithm, which is constructed by the combination of multi‐objective bee algorithms and Levy flight (LF) random walk is proposed to deal with the deployment problem in WSNs. For this purpose, two of the most important criteria, connectivity and coverage, have been considered as objectives. A series of experiments are carried out in large‐scale non‐uniform 3D environments, despite the fact that most of the present methods are applicable in small‐scale uniform 2D environments. This study completely takes into account the stochastic behaviour of swarms, something that other papers do not consider. The evaluation results show that the multi‐objective LF bee algorithm, in most cases, surpasses NSGAII, IBEA and SPEA2 algorithms.