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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.

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The lifetime comparison of MOCHs with different protocols in terms of rounds with different initial energies of the deployed sensor nodes. (a) The analysis of the network lifetime with the number of alive nodes; (b) The evaluation of the network lifetime with different energies.
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sensors-17-00440-f011: The lifetime comparison of MOCHs with different protocols in terms of rounds with different initial energies of the deployed sensor nodes. (a) The analysis of the network lifetime with the number of alive nodes; (b) The evaluation of the network lifetime with different energies.

Mentions: Figure 11a illustrates the lifetime comparison of the proposed model against the state-of-the-art clustering protocols like SEED, ABC, CEEC, and ZBR. Here, we discuss the lifetime of the network, which is defined as the time interval in which all the sensor nodes in the network drain their batteries. All the sensor nodes in the network of MOCHs, SEED, ABC, ZBR, and CEEC run out of batteries at about 4999, 3934, 2369, 1400, and 2954 rounds, respectively. The lifetime of the proposed model is approximately 1095, 2630, 3599, and 2045 greater than SEED, ABC, ZBR, and CEEC, respectively. The lifetime of the proposed model is approximately , , , and rounds greater than SEED, ABC, ZBR, and CEEC, respectively. The lifetime of MOCHs is greater than SEED because the CH selection criterion is marginally better in SEED, which restricts the number of the cluster to a certain limit due to that no extra CHs are selected. In the clustering protocols, the good selection criterion for the CHs selection saves a lot of energy in the network. The cluster formation mechanism is distributed in three different zones, no extra time and energy are consumed for repeated CH selection and cluster formation. In MOCHs, the optimal CH selection is done by the BS which contains unlimited resources and helps to save the energy of the network. The cluster formation involves a lot of processing and consumes the energy of the network. In SEED this selection is completed by CH and consumes almost of the network resources, which decreases the lifetime of SEED. The lifetime of ZBR is lesser than the proposed model because in ZBR the multi-hop communication is used to forward the data from the CH to the BS. The BS is placed outside the sensing field in any arbitrary place. The CHs closer to the BS relay the data of almost 3 back clusters. Consequently, the CHs closer to the BS run out of battery very quickly compared to the distant CHs which make the network unstable. Figure 11b depicts the network lifetime of MOCHs, SEED, ABC, CEEC, and ZBR with different network energies like 0.25 J, 0.75 J, and 1 J. We can see that the proposed models’ performance also remains very good at different network energies. We also compare the lifetime of the network with varying the node distribution. The Table 2 and Table 3 demonstrate the comparison of the lifetime of the network with and . From the tables, we can see that the proposed model outperforms as compared to SEED, ABC, CEEC, and ZBR in all the distribution scenarios.


Markov Chain Model-Based Optimal Cluster Heads Selection for Wireless Sensor Networks
The lifetime comparison of MOCHs with different protocols in terms of rounds with different initial energies of the deployed sensor nodes. (a) The analysis of the network lifetime with the number of alive nodes; (b) The evaluation of the network lifetime with different energies.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

sensors-17-00440-f011: The lifetime comparison of MOCHs with different protocols in terms of rounds with different initial energies of the deployed sensor nodes. (a) The analysis of the network lifetime with the number of alive nodes; (b) The evaluation of the network lifetime with different energies.
Mentions: Figure 11a illustrates the lifetime comparison of the proposed model against the state-of-the-art clustering protocols like SEED, ABC, CEEC, and ZBR. Here, we discuss the lifetime of the network, which is defined as the time interval in which all the sensor nodes in the network drain their batteries. All the sensor nodes in the network of MOCHs, SEED, ABC, ZBR, and CEEC run out of batteries at about 4999, 3934, 2369, 1400, and 2954 rounds, respectively. The lifetime of the proposed model is approximately 1095, 2630, 3599, and 2045 greater than SEED, ABC, ZBR, and CEEC, respectively. The lifetime of the proposed model is approximately , , , and rounds greater than SEED, ABC, ZBR, and CEEC, respectively. The lifetime of MOCHs is greater than SEED because the CH selection criterion is marginally better in SEED, which restricts the number of the cluster to a certain limit due to that no extra CHs are selected. In the clustering protocols, the good selection criterion for the CHs selection saves a lot of energy in the network. The cluster formation mechanism is distributed in three different zones, no extra time and energy are consumed for repeated CH selection and cluster formation. In MOCHs, the optimal CH selection is done by the BS which contains unlimited resources and helps to save the energy of the network. The cluster formation involves a lot of processing and consumes the energy of the network. In SEED this selection is completed by CH and consumes almost of the network resources, which decreases the lifetime of SEED. The lifetime of ZBR is lesser than the proposed model because in ZBR the multi-hop communication is used to forward the data from the CH to the BS. The BS is placed outside the sensing field in any arbitrary place. The CHs closer to the BS relay the data of almost 3 back clusters. Consequently, the CHs closer to the BS run out of battery very quickly compared to the distant CHs which make the network unstable. Figure 11b depicts the network lifetime of MOCHs, SEED, ABC, CEEC, and ZBR with different network energies like 0.25 J, 0.75 J, and 1 J. We can see that the proposed models’ performance also remains very good at different network energies. We also compare the lifetime of the network with varying the node distribution. The Table 2 and Table 3 demonstrate the comparison of the lifetime of the network with and . From the tables, we can see that the proposed model outperforms as compared to SEED, ABC, CEEC, and ZBR in all the distribution scenarios.

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.