Load balanced and optimal clustering in WSNs using grey wolf optimizer

被引:0
作者
Lekhraj [1 ,2 ]
Kumar, Alok [2 ]
Kumar, Anoj [2 ]
机构
[1] GLA Univ, Dept Comp Engn & Applicat, Mathura, India
[2] MNNIT Allahabad, Dept Comp Engn, Prayagraj, India
关键词
Clustering; LEACH; WSN; GWO; WIRELESS SENSOR NETWORKS; ENERGY-EFFICIENT; ROUTING ALGORITHM; PROTOCOL; SCHEME; HYBRID;
D O I
10.1007/s13198-024-02306-x
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A network of wireless sensors (WSN) is an outstanding technology that can aid in the various applications. Batteries run the sensor nodes those are used in WSN. The battery is impossible to charge or repair, so the most valuable resource for wireless sensor networks is power. Over the years, several strategies have been invented and used to preserve this precious WSN resource. One of the most successful approach for this purpose has turned out to be clustering. The aim of this paper is to suggest an effective technique for choosing cluster heads in WSNs to increase the lifetime of the network. To accomplish this task, Grey Wolf Optimizer (GWO) technique has been used. The general GWO was updated in this paper to meet the particular purpose of cluster head selection in WSNs. In this article, we have considered eleven attributes in the fitness function for the proposed algorithm. The simulation is carried out under different conditions. The results obtained show that the proposed protocol is superior in terms of energy consumption and network lifetime by evaluating the proposed protocol (i.e. CH-GWO protocol) with some well-existing cluster protocols. The suggested protocol forms energy-efficient and scalable clusters.
引用
收藏
页码:2950 / 2964
页数:15
相关论文
共 38 条
[1]   A survey on clustering algorithms for wireless sensor networks [J].
Abbasi, Ameer Ahmed ;
Younis, Mohamed .
COMPUTER COMMUNICATIONS, 2007, 30 (14-15) :2826-2841
[2]   GWO-C: Grey wolf optimizer-based clustering scheme for WSNs [J].
Agrawal, Deepika ;
Qureshi, Wasim Muhammad Huzaif ;
Pincha, Pooja ;
Srivastava, Prateet ;
Agarwal, Sourabh ;
Tiwari, Vikram ;
Pandey, Sudhakar .
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2020, 33 (08)
[3]   Wireless sensor networks: a survey [J].
Akyildiz, IF ;
Su, W ;
Sankarasubramaniam, Y ;
Cayirci, E .
COMPUTER NETWORKS, 2002, 38 (04) :393-422
[4]  
[Anonymous], 2011, 2011 INT C COMP MAN
[5]  
[Anonymous], 2005, P INT C COMP INT MEA
[6]  
Baker D. J., 1984, IEEE Journal on Selected Areas in Communications, VSAC-2, P226, DOI 10.1109/JSAC.1984.1146043
[7]   An energy-efficient ant-based routing algorithm for wireless sensor networks [J].
Camilo, Tiago ;
Carreto, Carlos ;
Silva, Jorge Sa ;
Boavida, Fernando .
ANT COLONY OPTIMIZATION AND SWARM INTELLIGENCE, PROCEEDINGS, 2006, 4150 :49-59
[8]   Design and analysis of a fast local clustering service for wireless sensor networks [J].
Demirbas, M ;
Arora, A ;
Mittal, V ;
Kulathumani, V .
FIRST INTERNATIONAL CONFERENCE ON BROADBAND NETWORKS, PROCEEDINGS, 2004, :700-709
[9]  
Ding P, 2005, Distributed energy-efficient hierarchical clustering for wireless sensor networks, distributed computing in sensor systems, P466
[10]  
Gupta V., 2014, ADV INTELLIGENT SYST, P11, DOI 10.1007/978-81-322-2217-0_2