Energy-Balanced Cluster-Routing Protocol Based on Particle Swarm Optimization with Five Mutation Operators for Wireless Sensor Networks

被引:14
作者
Han, Yamin [1 ]
Byun, Heejung [2 ]
Zhang, Liangliang [1 ]
机构
[1] Univ Suwon, Dept Comp Sci, Hwaseong 18323, South Korea
[2] Univ Suwon, Dept Informat & Technol, Hwaseong 18323, South Korea
基金
新加坡国家研究基金会;
关键词
wireless sensor networks; cluster; energy balance; particle swarm optimization; mutation operators; MOBILE SINK; ALGORITHM; LIFETIME; LEACH;
D O I
10.3390/s20247217
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Prolonging the network lifetime is one of the fundamental requirements in wireless sensor networks (WSNs). Sensor node clustering is a very popular energy conservation strategy in WSNs, allowing to achieve energy efficiency, low latency, and scalability. According to this strategy, sensor nodes are grouped into several clusters, and one sensor node in each cluster is assigned to be a cluster head (CH). The responsibility of each CH is to aggregate data from the other sensor nodes within its cluster and send these data to the sink. However, the distribution of sensor nodes in the sensing region is often non-uniform, which may lead to an unbalanced number of sensor nodes between clusters and thus unbalanced energy consumption between CHs. This, in turn, may result in a reduced network lifetime. Furthermore, a different number of clusters lead to a different quality of service of a WSN system. To address the problems of unbalanced number of sensor nodes between clusters and selecting an optimal number of clusters, this study proposes an energy-balanced cluster-routing protocol (EBCRP) based on particle swarm optimization (PSO) with five mutation operators for WSNs. The five mutation operators are specially proposed to improve the performance of PSO in optimizing sensor node clustering. A rotation CH selection scheme based on the highest residual energy is used to dynamically select a CH for each cluster in each round. Simulation results show that the proposed EBCRP method performs well in balancing energy consumption and prolonging the network lifetime.
引用
收藏
页码:1 / 20
页数:20
相关论文
共 44 条
[1]   Joint Optimization of Transmission Power Level and Packet Size for WSN Lifetime Maximization [J].
Akbas, Ayhan ;
Yildiz, Huseyin Ugur ;
Tavli, Bulent ;
Uludag, Suleyman .
IEEE SENSORS JOURNAL, 2016, 16 (12) :5084-5094
[2]   Data Gathering in Delay Tolerant Wireless Sensor Networks Using a Ferry [J].
Alnuaimi, Mariam ;
Shuaib, Khaled ;
Alnuaimi, Klaithem ;
Abdel-Hafez, Mohammed .
SENSORS, 2015, 15 (10) :25809-25830
[3]   Energy conservation in wireless sensor networks: A survey [J].
Anastasi, Giuseppe ;
Conti, Marco ;
Di Francesco, Mario ;
Passarella, Andrea .
AD HOC NETWORKS, 2009, 7 (03) :537-568
[4]  
[Anonymous], 2013, INT J ADV RES COMPUT
[5]  
[Anonymous], 2013, J BASIC APPL SCI RES
[6]  
Bhadeshiya J. R., 2012, J INFORM KNOWLEDGE R, V2, P812
[7]   General network lifetime and cost models for evaluating sensor network deployment strategies [J].
Cheng, Zhao ;
Perillo, Mark ;
Heinzelman, Wendi B. .
IEEE TRANSACTIONS ON MOBILE COMPUTING, 2008, 7 (04) :484-497
[8]   A Pareto optimization-based approach to clustering and routing in Wireless Sensor Networks [J].
Elhabyan, Riham ;
Shi, Wei ;
St-Hilaire, Marc .
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2018, 114 :57-69
[9]   Cluster-based routing protocols in wireless sensor networks: A survey based on methodology [J].
Fanian, Fakhrosadat ;
Rafsanjani, Marjan Kuchaki .
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2019, 142 :111-142
[10]   A Survey on Underwater Wireless Sensor Networks: Requirements, Taxonomy, Recent Advances, and Open Research Challenges [J].
Fattah, Salmah ;
Gani, Abdullah ;
Ahmedy, Ismail ;
Idris, Mohd Yamani Idna ;
Hashem, Ibrahim Abaker Targio .
SENSORS, 2020, 20 (18) :1-30