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An information entropy based-clustering algorithm for heterogeneous wireless sensor networks - 2018

Research Area:  Wireless Sensor Networks


This paper proposes a novel dynamic, distributive, and self-organizing entropy based clustering scheme that benefits from the local information of sensor nodes measured in terms of entropy and use that as criteria for cluster head election and cluster formation. It divides the WSN into two-levels of hierarchy and three-levels of energy heterogeneity of sensor nodes. The simulation results reveal that the proposed approach outperforms existing baseline algorithms in terms of energy consumption, stability period, and the network lifetime.

Author(s) Name:  Walid Osamy, Ahmed Salim and Ahmed M. Khedr

Journal name:  Wireless Networks

Conferrence name:  

Publisher name:  Springer

DOI:  10.1007/s11276-018-1877-y

Volume Information:  volume 26, pages 1869–1886 (2020)