A hybrid firefly algorithm with particle swarm optimization for energy efficient optimal cluster head selection in wireless sensor networks

被引:0
作者
B. Pitchaimanickam
G. Murugaboopathi
机构
[1] Kalasalingam Academy of Research and Education,Department of Computer Science and Engineering
来源
Neural Computing and Applications | 2020年 / 32卷
关键词
Wireless Sensor Networks; LEACH-C Algorithm; Firefly Algorithm (FA); Particle Swarm Optimization (PSO); Network lifetime; Energy consumption;
D O I
暂无
中图分类号
学科分类号
摘要
Wireless Sensor Networks (WSN) are operated on battery source, and the sensor nodes are used for collecting the information from the environment and transmitting the same to the base station. The sensor nodes consume more energy for the process of data communication and also affect the network lifetime. Energy efficiency is one of the important features for designing the sensor networks. Clustering technique is mainly used to perform the energy-efficient data transmission that consumes the minimum energy and also prolongs the lifetime of the network. In this paper, a Hybrid approach of Firefly Algorithm with Particle Swarm Optimization (HFAPSO) is proposed for finding the optimal cluster head selection in the LEACH-C algorithm. The hybrid algorithm improves the global search behavior of fireflies by using PSO and achieves optimal positioning of the cluster heads. The performance of the proposed methodology is evaluated by using the number of alive nodes, residual energy and throughput. The results show the improvement in network lifetime, thus increasing the alive nodes and reducing the energy utilization. While making a comparison with the firefly algorithm, it has been found that the proposed methodology has achieved better throughput and residual energy.
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页码:7709 / 7723
页数:14
相关论文
共 81 条
[1]  
Ahmed AA(2017)Churn prediction on huge telecom data using hybrid firefly based classification Egypt Inf J 18 215-220
[2]  
Maheswari D(2002)A survey on sensor networks IEEE Commun Mag 40 102-114
[3]  
Akyildiz IF(2013)Energy constraint clustering algorithms for wireless sensor networks AdHoc Netw 11 2512-2525
[4]  
Su W(2013)An energy aware fuzzy approach to unequal clustering in wireless sensor networks Appl Soft Comput 13 1741-1749
[5]  
Sankarasubramaniam Y(2018)Integrated clustering and routing protocol for wireless sensor networks using Cuckoo and Harmony Search based metaheuristic techniques Eng Appl Artif Intell 68 101-109
[6]  
Cayirci E(2002)An application-specific protocol architecture for wireless micro sensor networks IEEE Trans Wirel Commun 1 660-670
[7]  
Albath J(2007)Biologically inspired cooperative routing for wireless mobile sensor networks IEEE Syst J 1 29-37
[8]  
Thakur M(2008)EEMC: an energy-efficient multi-level clustering algorithm for large-scale wireless sensor networks Comput Netw 52 542-562
[9]  
Madria S(2016)Hybrid firefly and Particle Swarm Optimization algorithm for the detection of Bundle Branch Block International Journal of Cardiovascular Academy 2 44-48
[10]  
Bagci H(2014)Energy efficient clustering and routing algorithms for wireless sensor networks: particle swarm optimization approach Eng Appl Artif Intell 33 127-140