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Markov Chain Model-Based Optimal Cluster Heads Selection for Wireless 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.

No MeSH data available.


The comparison of total number of CHs selected per round in the lifetime of the network of MOCHs with different protocols. (a) The analysis of number of CHs per in the network; (b) The effect of different of number of CHs on the network.
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sensors-17-00440-f014: The comparison of total number of CHs selected per round in the lifetime of the network of MOCHs with different protocols. (a) The analysis of number of CHs per in the network; (b) The effect of different of number of CHs on the network.

Mentions: The nodes in the sensing field are installed through the distributed algorithm. Therefore, the distributions of nodes in the sensing field are not even. The previously designed clustering protocols use the distributed clustering algorithm for CH selection, which increases the computational overhead on all the nodes. Another problem is that the optimum numbers of CHs are also not guaranteed through this distributed algorithm. If the selected number of CHs is not optimal, this causes the resources to deplete very quickly. In this proposed model, we introduce a new mechanism which restricts the algorithm to select the optimal number of CHs in each round. Figure 14a depicts the comparison of the number of CHs selected per round in SEED, ABC, CEEC, and ZBR. The proposed model always chooses the optimal number of CHs in comparison with selected state-of-the-art clustering protocols. While the other clustering protocol selects the CHs through distributed algorithm, so, their selection criterion is not very good. Consequently, the number of CHs in ZBR and ABC vary from 10%–50% CHs per round during the lifetime of the network. The performance of our algorithm remains very consistent when we increase the node densities from to , it always meets the optimality criterion for CHs selection as depicted in Figure 14b.


Markov Chain Model-Based Optimal Cluster Heads Selection for Wireless Sensor Networks
The comparison of total number of CHs selected per round in the lifetime of the network of MOCHs with different protocols. (a) The analysis of number of CHs per in the network; (b) The effect of different of number of CHs on the network.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5375726&req=5

sensors-17-00440-f014: The comparison of total number of CHs selected per round in the lifetime of the network of MOCHs with different protocols. (a) The analysis of number of CHs per in the network; (b) The effect of different of number of CHs on the network.
Mentions: The nodes in the sensing field are installed through the distributed algorithm. Therefore, the distributions of nodes in the sensing field are not even. The previously designed clustering protocols use the distributed clustering algorithm for CH selection, which increases the computational overhead on all the nodes. Another problem is that the optimum numbers of CHs are also not guaranteed through this distributed algorithm. If the selected number of CHs is not optimal, this causes the resources to deplete very quickly. In this proposed model, we introduce a new mechanism which restricts the algorithm to select the optimal number of CHs in each round. Figure 14a depicts the comparison of the number of CHs selected per round in SEED, ABC, CEEC, and ZBR. The proposed model always chooses the optimal number of CHs in comparison with selected state-of-the-art clustering protocols. While the other clustering protocol selects the CHs through distributed algorithm, so, their selection criterion is not very good. Consequently, the number of CHs in ZBR and ABC vary from 10%–50% CHs per round during the lifetime of the network. The performance of our algorithm remains very consistent when we increase the node densities from to , it always meets the optimality criterion for CHs selection as depicted in Figure 14b.

View Article: PubMed Central - PubMed

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.

No MeSH data available.