Load balanced clustering scheme using hybrid metaheuristic technique for mobile sink based wireless sensor networks

Fundamental design goal of a typical wireless sensor network is to optimize energy consumption. Recent studies have confirmed that node clustering mechanism efficiently utilizes energy resource of the network by organizing nodes into a set of clusters and helps in extending the network lifetime. Mos...

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Bibliographic Details
Published in:Journal of ambient intelligence and humanized computing Vol. 13; no. 11; pp. 5283 - 5294
Main Authors: Gupta, Govind P., Saha, Binit
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2022
Springer Nature B.V
Subjects:
Algorithms
Artificial Intelligence
Bees
Clustering
Computational Intelligence
Energy consumption
Energy sources
Engineering
Evolutionary computation
Heuristic
Heuristic methods
Linear programming
Load balancing
Nodes
Original Research
Performance evaluation
Residual energy
Robotics and Automation
Sensors
Swarm intelligence
User Interfaces and Human Computer Interaction
Wireless sensor networks
Differential evolution
Mobile sink
Artificial bee colony
Clustering
ISSN:1868-5137, 1868-5145
Online Access:Get full text
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Summary:Fundamental design goal of a typical wireless sensor network is to optimize energy consumption. Recent studies have confirmed that node clustering mechanism efficiently utilizes energy resource of the network by organizing nodes into a set of clusters and helps in extending the network lifetime. Most of the existing node clustering schemes suffers from non-uniform distribution of cluster heads, unbalanced load problem among clusters and left-out node issues. In order to solve these issues, we have focused on to design a load-balanced clustering scheme which also resolves the left-out nodes problem. This study proposes a hybrid meta-heuristic technique where best features of Artificial Bee Colony and Differential Evolution are combined to evaluate the best set of load-balanced cluster heads. For energy efficient and load-balanced clustering, a novel objective function is derived based on average energy, intra-cluster distance and delay parameters. Following this, Artificial Bee Colony based meta-heuristic algorithm is proposed for the dynamic re-localization of the mobile sink within a cluster-based network infrastructure. Performance comparison of the proposed scheme with the existing three well known schemes is evaluated under different network scenarios. Simulation results validate that the proposed scheme performs better in terms of average energy consumption, total energy consumption, residual energy, and network lifetime.
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ISSN:1868-5137
1868-5145
DOI:10.1007/s12652-020-01909-z