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

被引:4
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 48 条
[31]   Gradient-Based Routing for Energy Consumption Balance in Multiple Sinks-based Wireless Sensor Networks [J].
Migabo, M. E. ;
Djouani, K. ;
Kurien, A. M. ;
Olwal, T. O. .
6TH INTERNATIONAL CONFERENCE ON EMERGING UBIQUITOUS SYSTEMS AND PERVASIVE NETWORKS (EUSPN 2015)/THE 5TH INTERNATIONAL CONFERENCE ON CURRENT AND FUTURE TRENDS OF INFORMATION AND COMMUNICATION TECHNOLOGIES IN HEALTHCARE (ICTH-2015), 2015, 63 :488-493
[32]   Proposed Energy Efficient Algorithm for Clustering and Routing in WSN [J].
Morsy, Nehad A. ;
AbdelHay, Ehab H. ;
Kishk, Sherif S. .
WIRELESS PERSONAL COMMUNICATIONS, 2018, 103 (03) :2575-2598
[33]  
Nigam G. K., 2018, J KING SAUD UNIV-COM
[34]   SIMULATED ANNEALING FOR PERMUTATION FLOWSHOP SCHEDULING [J].
OSMAN, IH ;
POTTS, CN .
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 1989, 17 (06) :551-557
[35]   Improved energy efficient WSN using ACO based HSA for optimal cluster head selection [J].
Poonguzhali, P. K. ;
Ananthamoorthy, N. P. .
PEER-TO-PEER NETWORKING AND APPLICATIONS, 2020, 13 (04) :1102-1108
[36]   Lifetime Improvement in Wireless Sensor Networks using Hybrid Differential Evolution and Simulated Annealing (DESA) [J].
Potthuri, Sweta ;
Shankar, T. ;
Rajesh, A. .
AIN SHAMS ENGINEERING JOURNAL, 2018, 9 (04) :655-663
[37]   On improving the lifespan of wireless sensor networks with fuzzy based clustering and machine learning based data reduction [J].
Radhika, S. ;
Rangarajan, P. .
APPLIED SOFT COMPUTING, 2019, 83
[38]   A lot streaming based flow shop scheduling problem using simulated annealing algorithm [J].
Ramesh, C. ;
Kamalakannan, R. ;
Karthik, R. ;
Pavin, C. ;
Dhivaharan, S. .
MATERIALS TODAY-PROCEEDINGS, 2021, 37 :241-244
[39]  
Ramluckun N., 2020, Applied Computing and Informatics, V16, P39, DOI 10.1016/j.aci.2018.02.004
[40]  
Shabbir N., 2017, Wireless Sensor Networks-Insights and Innovations, DOI [10.5772/intechopen.70208, DOI 10.5772/INTECHOPEN.70208]