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Sensors 2017, 17(3), 440; doi:10.3390/s17030440

Markov Chain Model-Based Optimal Cluster Heads Selection for Wireless Sensor Networks

1
School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China
2
School of Management, Xi’an Jiaotong University, Xi’an 710049, China
*
Authors to whom correspondence should be addressed.
Academic Editor: Mohamed F. Younis
Received: 29 November 2016 / Revised: 7 February 2017 / Accepted: 17 February 2017 / Published: 23 February 2017
(This article belongs to the Section Sensor Networks)
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Abstract

The longer network lifetime of Wireless Sensor Networks (WSNs) is a goal which is directly related to energy consumption. This energy consumption issue becomes more challenging when the energy load is not properly distributed in the sensing area. The hierarchal clustering architecture is the best choice for these kind of issues. In this paper, we introduce a novel clustering protocol called Markov chain model-based optimal cluster heads (MOCHs) selection for WSNs. In our proposed model, we introduce a simple strategy for the optimal number of cluster heads selection to overcome the problem of uneven energy distribution in the network. The attractiveness of our model is that the BS controls the number of cluster heads while the cluster heads control the cluster members in each cluster in such a restricted manner that a uniform and even load is ensured in each cluster. We perform an extensive range of simulation using five quality measures, namely: the lifetime of the network, stable and unstable region in the lifetime of the network, throughput of the network, the number of cluster heads in the network, and the transmission time of the network to analyze the proposed model. We compare MOCHs against Sleep-awake Energy Efficient Distributed (SEED) clustering, Artificial Bee Colony (ABC), Zone Based Routing (ZBR), and Centralized Energy Efficient Clustering (CEEC) using the above-discussed quality metrics and found that the lifetime of the proposed model is almost 1095, 2630, 3599, and 2045 rounds (time steps) greater than SEED, ABC, ZBR, and CEEC, respectively. The obtained results demonstrate that the MOCHs is better than SEED, ABC, ZBR, and CEEC in terms of energy efficiency and the network throughput. View Full-Text
Keywords: Markov chain-based model; optimal number; multi-hop routing; non-associated nodes; energy efficiency Markov chain-based model; optimal number; multi-hop routing; non-associated nodes; energy efficiency
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Ahmed, G.; Zou, J.; Zhao, X.; Sadiq Fareed, M.M. Markov Chain Model-Based Optimal Cluster Heads Selection for Wireless Sensor Networks. Sensors 2017, 17, 440.

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