Title: Parallel cuckoo search for cognitive wireless sensor networks

Authors: Tong-Bang Jiang; Jeng-Shyang Pan; Yu-Mo Gu; Shu-Chuan Chu

Addresses: Department of Intelligence Science and Technology, Dalian Maritime University, Dalian, 116026, China ' College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, China ' Department of Intelligence Science and Technology, Dalian Maritime University, Dalian, 116026, China ' College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, China

Abstract: In cognitive wireless sensor networks (CWSNs), the limited energy of the sensor node is the core defect that restricts its comprehensive network performance. This paper proposes a parallel cuckoo search medoids (PCS-medoids) algorithm to manage the energy consumption in CWSNs efficiently. Firstly, a parallel cuckoo search algorithm (PCS) with communication is proposed to speed up the convergence of CS. Then, the PCS is applied to k-medoids to get cluster heads quickly. Finally, the PCS-medoids is presented to manage the consumption of sensor nodes. First experimental results illustrate that PCS tends to get optimal solutions quickly and accurately compared to CS and PSO. The other experimental results demonstrate that PCS-medoids has advantages over energy management in CWSNs compared to low-energy adaptive clustering hierarchy, LEACH-centralised, and hybrid energy-efficient distributed clustering. Besides, the ad-vantages are more obvious with the increase of sensor nodes in CWSNs.

Keywords: CWSNs; cognitive wireless sensor networks; limited energy; communication; parallel cuckoo search; cluster heads; PCS-medoids; parallel cuckoo search medoids; energy management.

DOI: 10.1504/IJSNET.2021.113846

International Journal of Sensor Networks, 2021 Vol.35 No.3, pp.193 - 205

Received: 19 Jul 2020
Accepted: 30 Jul 2020

Published online: 24 Mar 2021 *

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