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Issue title: Special section: Recent trends, Challenges and Applications in Cognitive Computing for Intelligent Systems
Guest editors: Vijayakumar Varadarajan, Piet Kommers, Vincenzo Piuri and V. Subramaniyaswamy
Article type: Research Article
Authors: Agrawal, Deepikaa; * | Pandey, Sudhakara | Gupta, Punitb | Kumar Goyal, Mayankc
Affiliations: [a] Department of Information Technology, National Institute of Technology Raipur, Amanaka, Raipur, Chhattisgarh, India | [b] Department of Computer and Communication Engineering, Manipal University Jaipur, Rajasthan, India | [c] Department of Computer Science and Engineering, Sharda University, Greater Noida, Uttar Pradesh, India
Correspondence: [*] Corresponding author. Deepika Agrawal, Department of Information Technology, National Institute of Technology Raipur, Great Eastern Rd, Amanaka, Raipur, Chhattisgarh 492010, India. E-mail: [email protected].
Abstract: Wireless Sensor Networks is a complex network with millions of small-scale sensor nodes, working together to detect certain physical phenomena. Sensor nodes are operated by battery therefore the major concern is energy efficiency. Clustering is an effective technique to decrease the energy depletion in the network. However, choosing the optimum Cluster Heads is an NP-Hard problem. This paper proposes an unequal clustering technique that selects probationary Cluster Heads through fuzzy logic and the optimization of this probationary Cluster Heads is done through Harmony Search Algorithm (HSA). The proposed algorithm exhibits the dynamic capability of fuzzy logic and high search efficiency of HSA that extends the network lifespan. The findings are simulated against traditional clustering protocols and compared. The findings obtained show that the protocol proposed is performing superior in terms of network lifespan prolongation and other metrics.
Keywords: Optimal cluster heads, optimization, harmony search algorithm, wireless sensor networks, unequal clustering
DOI: 10.3233/JIFS-189175
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 6, pp. 8587-8597, 2020
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