Node deployment in wireless sensor networks using the new multi-objective Levy flight bee algorithm

被引:10
|
作者
Hajizadeh, Nahid [1 ]
Javidan, Reza [1 ]
Shamsinejad, Pirooz [1 ]
Akbari, Reza [1 ]
机构
[1] Shiraz Univ Technol, Dept Comp Engn & Informat Technol, Shiraz, Iran
关键词
wireless sensor networks; genetic algorithms; Pareto optimisation; search problems; computational complexity; small-scale uniform environments; hybrid multiobjective optimisation algorithm; multiobjective bee algorithms; Levy flight random walk; deployment problem; WSNs; large-scale nonuniform 3D environments; small-scale uniform 2D environments; multiobjective LF bee algorithm; SPEA2; algorithms; node deployment; multiobjective Levy flight bee algorithm; computer networks; basic network services; conflicting optimisation factors; sophisticated issue; NP-complete problem; single-objective metaheuristic algorithms; COLONY OPTIMIZATION; MODEL;
D O I
10.1049/iet-wss.2019.0083
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
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.
引用
收藏
页码:78 / 87
页数:10
相关论文
共 50 条
  • [1] Relay node deployment for wireless sensor networks using evolutionary multi-objective algorithm
    Wang, Qiang
    Liu, Hai-Lin
    Gu, Fangqing
    [J]. INTERNATIONAL JOURNAL OF SENSOR NETWORKS, 2019, 31 (03) : 189 - 197
  • [2] Relay node deployment for wireless sensor networks using evolutionary multi-objective algorithm
    Wang, Qiang
    Liu, Hai-Lin
    Gu, Fangqing
    [J]. International Journal of Sensor Networks, 2019, 31 (03): : 189 - 197
  • [3] Constrained Relay Node Deployment using an improved multi-objective Artificial Bee Colony in Wireless Sensor Networks
    Yu, Wenjie
    Li, Xunbo
    Li, Xiang
    Zeng, Zhi
    [J]. KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, 2017, 11 (06): : 2889 - 2909
  • [4] Node deployment for wireless sensor networks based on improved multi-objective evolutionary algorithm
    [J]. Wei, Kaibin (kaibinwei@21cn.com), 1600, Inderscience Publishers, 29, route de Pre-Bois, Case Postale 856, CH-1215 Geneva 15, CH-1215, Switzerland (10):
  • [5] Wireless sensor network node deployment based on multi-objective immune algorithm
    Li, Shanshan
    [J]. INTERNATIONAL JOURNAL OF INTERNET PROTOCOL TECHNOLOGY, 2018, 11 (01) : 12 - 18
  • [6] A Novel Sensor Deployment Approach Using Multi-Objective Imperialist Competitive Algorithm in Wireless Sensor Networks
    Enayatifar, Rasul
    Yousefi, Moslem
    Abdullah, Abdul Hanan
    Darus, Amer Nordin
    [J]. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2014, 39 (06) : 4637 - 4650
  • [7] A Novel Sensor Deployment Approach Using Multi-Objective Imperialist Competitive Algorithm in Wireless Sensor Networks
    Rasul Enayatifar
    Moslem Yousefi
    Abdul Hanan Abdullah
    Amer Nordin Darus
    [J]. Arabian Journal for Science and Engineering, 2014, 39 : 4637 - 4650
  • [8] An Evolutionary Algorithm to a Multi-Objective Deployment and Power Assignment Problem in Wireless Sensor Networks
    Konstantinidis, Andreas
    Yang, Kun
    Zhang, Qingfu
    [J]. GLOBECOM 2008 - 2008 IEEE GLOBAL TELECOMMUNICATIONS CONFERENCE, 2008,
  • [9] A multi-objective evolutionary algorithm for the deployment and power assignment problem in wireless sensor networks
    Konstantinidis, Andreas
    Yang, Kun
    Zhang, Qingfu
    Zeinalipour-Yazti, Demetrios
    [J]. COMPUTER NETWORKS, 2010, 54 (06) : 960 - 976
  • [10] Controlled Deployment in Wireless Sensor Networks based on a Novel Multi Objective Bee Swarm Optimization Algorithm
    Hajizadeh, Nahid
    Jahanbazi, Peyman
    Javidan, Reza
    [J]. 2018 3RD CONFERENCE ON SWARM INTELLIGENCE AND EVOLUTIONARY COMPUTATION (CSIEC2018), VOL 3, 2018, : 30 - 36