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A dynamic harmony search-based fuzzy clustering protocol for energy-efficient wireless sensor networks


In the development of cluster-based energy-efficient protocols for wireless sensor networks (WSNs), a particularly challenging problem is the dynamic organization of sensors into a wireless communication network and the routing of sensed information from the field sensors to a remote base station (BS) in a manner that prolongs the lifetime of WSNs. This paper presents a new energy-efficient clustering protocol for WSNs, which can minimize total network energy dissipation while maximizing network lifetime. The protocol is divided into two parts. The first deals with constructing an infrastructure for the given WSN. A newly developed algorithm, based on a harmony search (HS), automatically determines the optimal number of clusters and allocates sensors into these clusters. This algorithm also eliminates the need to set the number of clusters a priori. The second part is concerned with the process of sending sensed data from nodes to their cluster head and then to the BS. A decentralized fuzzy clustering algorithm is proposed, where the selection of cluster heads in each round is locally made in each cluster during the network lifetime. Simulation results demonstrate that the proposed protocol can achieve an optimal number of clusters, prolong the network lifetime and increase the data delivery at the BS, when compared to other well-known clustering-based routing protocols.

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    The initial version of the proposed protocol, which was presented in [46]

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    The initial version of the proposed objective function was presented in [46, 53]


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The author gratefully acknowledges the support received in the course of this study from the Sensor Networks and Cellular Systems Research Center, the University of Tabuk, and the Ministry of Education in Saudi Arabia.

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Correspondence to Osama Moh’d Alia.

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Alia, O.M. A dynamic harmony search-based fuzzy clustering protocol for energy-efficient wireless sensor networks. Ann. Telecommun. 73, 353–365 (2018).

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  • Wireless sensor networks
  • Energy-efficient routing protocols
  • Harmony search algorithm
  • Fuzzy clustering