Lifetime Optimization of the LEACH Protocol in WSNs with Simulated Annealing Algorithm

被引:3
|
作者
Gulbas, Gulsah [1 ]
Cetin, Gurcan [1 ]
机构
[1] Mugla Sitki Kocman Univ, Dept Informat Syst Engn, Mugla, Turkiye
关键词
LEACH protocol; Lifetime optimization; Simulated annealing; Wireless sensor networks; WIRELESS SENSOR NETWORKS; PARTICLE SWARM; PERFORMANCE; CLUSTER; GA;
D O I
10.1007/s11277-023-10746-0
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
The lifetime of a Wireless Sensor Network (WSN) is determined by its energy restriction. One of the conventional techniques used to maintain network connectivity is the utilization of the LEACH routing protocol. LEACH is based on clustering, and the process of choosing a Cluster Head (CH) in each round is based on chance. Consequently, it remains unclear whether the best CH is selected for each round. In this study, two approaches based on the Simulated Annealing (SA) algorithm are described to minimize energy losses of the nodes and improve the lifetime of the WSN utilizing the LEACH routing protocol. In both techniques, the residual energies at the nodes, as well as their distances from each other, are taken into consideration when determining the CHs. The efficiency of the presented approaches has been evaluated for networks with 10, 25, 50 and 100 sensors in terms of consumed energy, total data packets received by the Base Station (BS), the number of active/dead nodes, and the average energy per sensor. According to the findings, the PSCH-SA technique yields the most favorable results in networks with 10 sensors, while the LEACH-SA protocol demonstrates superior performance in WSNs with 25 or more sensors.
引用
收藏
页码:2857 / 2883
页数:27
相关论文
共 50 条
  • [31] A modification of the simulated annealing algorithm for discrete stochastic optimization
    Ahmed, Mohamed A.
    ENGINEERING OPTIMIZATION, 2007, 39 (06) : 701 - 714
  • [32] A new optimization algorithm of kinoforms based on simulated annealing
    Nozaki, Shinya
    Chen, Yen-Wei
    Nakao, Zensho
    KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS: KES 2007 - WIRN 2007, PT II, PROCEEDINGS, 2007, 4693 : 303 - 310
  • [33] Adaptive simulated annealing particle swarm optimization algorithm
    Yan Q.
    Ma R.
    Ma Y.
    Wang J.
    Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University, 2021, 48 (04): : 120 - 127
  • [34] A simulated annealing algorithm for transient optimization in gas networks
    Debora Mahlke
    Alexander Martin
    Susanne Moritz
    Mathematical Methods of Operations Research, 2007, 66 : 99 - 115
  • [35] Convergence of the Simulated Annealing Algorithm for Continuous Global Optimization
    R. L. Yang
    Journal of Optimization Theory and Applications, 2000, 104 : 691 - 716
  • [37] Simulated annealing algorithm involving chance constrained optimization
    Huang, Wei
    Lin, Xiaohui
    Wuhan Jiaotong Keji Daxue Xuebao/Journal of Wuhan Transportation University, 2000, 24 (02): : 195 - 199
  • [38] Machining sequencing optimization based on Simulated Annealing Algorithm
    Qiao, Lihong
    Hu, Quanwei
    Zhang, Hongwei
    ADVANCED MANUFACTURING TECHNOLOGY, PTS 1-4, 2012, 472-475 : 1632 - +
  • [39] A New Dynamic Simulated Annealing Algorithm for Global Optimization
    Yarmohamadi, Hasan
    Kabudian, Jahanshah
    Mirhosseini, Seyed Hanif
    JOURNAL OF MATHEMATICS AND COMPUTER SCIENCE-JMCS, 2015, 14 (01): : 16 - 23
  • [40] A simulated annealing algorithm for transient optimization in gas networks
    Mahlke, Debora
    Martin, Alexander
    Moritz, Susanne
    MATHEMATICAL METHODS OF OPERATIONS RESEARCH, 2007, 66 (01) : 99 - 115