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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 stable and unstable regions comparison of MOCHs with SEED, CEEC, ABC, and ZBR in the lifetime of the network. (a) The network stability comparison; (b) The analysis of energy consumption per round.
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sensors-17-00440-f012: The stable and unstable regions comparison of MOCHs with SEED, CEEC, ABC, and ZBR in the lifetime of the network. (a) The network stability comparison; (b) The analysis of energy consumption per round.

Mentions: The stability period is defined as, the time interval that begins when the first node depletes its battery. The Figure 12a depicts the comparison of stable and unstable regions of the proposed model with SEED, CEEC, ABC, and ZBR. The first nodes of the MOCHs, SEED, CEEC, ABC, and ZBR drain their batteries at about 3055, 2500, 1200, 1500, and 1100 rounds, respectively. The stability period of the proposed model is approximate , , , and greater than SEED, CEEC, ABC, and ZBR, respectively. The stability period is the time duration in which all the sensor nodes are alive and the performance of the network is maximum. The proposed model has very long stable period, because of the good energy management and good energy distribution among all the dynamic clusters. After that, the unstable region starts with the death of the first node. In an unstable region, the nodes run out of batteries and the performance of the network decreases gradually. The unstable period of the proposed model in comparison with SEED, CEEC, ABC, and ZBR is about 1945, 1434, 1754, 869, and 200 rounds greater, respectively. In ZBR due to multi-hop communication, the CHs closer to the BS run out of battery soon compared to the distant CHs. When the CHs closer to the BS deplete their batteries the network un-stabilizes for some time and collapses after 200 rounds. However, in SEED, ABC, and CEEC after the first node run out of battery and the network becomes unstable for the lifetime of the network due to uneven energy distribution. Figure 12b illustrates the network energy consumption of MOCHs, SEED, CEEC, ABC, and ZBR. The energy consumption of the proposed model is optimized and remains smooth in the whole network lifetime. The energy consumption is very low because MOCHs use the available power resources in very optimized and balanced way which increases its lifetime. The energy consumption of SEED is also balanced due to its even energy distribution in the network. The Table 4 and Table 5 reveal the comparison of the stable and unstable regions of the network with and . From the tables, we can see that the proposed model’s performance remains remarkable with different node densities as compared to SEED, CEEC, ABC, and ZBR.


Markov Chain Model-Based Optimal Cluster Heads Selection for Wireless Sensor Networks
The stable and unstable regions comparison of MOCHs with SEED, CEEC, ABC, and ZBR in the lifetime of the network. (a) The network stability comparison; (b) The analysis of energy consumption per round.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

sensors-17-00440-f012: The stable and unstable regions comparison of MOCHs with SEED, CEEC, ABC, and ZBR in the lifetime of the network. (a) The network stability comparison; (b) The analysis of energy consumption per round.
Mentions: The stability period is defined as, the time interval that begins when the first node depletes its battery. The Figure 12a depicts the comparison of stable and unstable regions of the proposed model with SEED, CEEC, ABC, and ZBR. The first nodes of the MOCHs, SEED, CEEC, ABC, and ZBR drain their batteries at about 3055, 2500, 1200, 1500, and 1100 rounds, respectively. The stability period of the proposed model is approximate , , , and greater than SEED, CEEC, ABC, and ZBR, respectively. The stability period is the time duration in which all the sensor nodes are alive and the performance of the network is maximum. The proposed model has very long stable period, because of the good energy management and good energy distribution among all the dynamic clusters. After that, the unstable region starts with the death of the first node. In an unstable region, the nodes run out of batteries and the performance of the network decreases gradually. The unstable period of the proposed model in comparison with SEED, CEEC, ABC, and ZBR is about 1945, 1434, 1754, 869, and 200 rounds greater, respectively. In ZBR due to multi-hop communication, the CHs closer to the BS run out of battery soon compared to the distant CHs. When the CHs closer to the BS deplete their batteries the network un-stabilizes for some time and collapses after 200 rounds. However, in SEED, ABC, and CEEC after the first node run out of battery and the network becomes unstable for the lifetime of the network due to uneven energy distribution. Figure 12b illustrates the network energy consumption of MOCHs, SEED, CEEC, ABC, and ZBR. The energy consumption of the proposed model is optimized and remains smooth in the whole network lifetime. The energy consumption is very low because MOCHs use the available power resources in very optimized and balanced way which increases its lifetime. The energy consumption of SEED is also balanced due to its even energy distribution in the network. The Table 4 and Table 5 reveal the comparison of the stable and unstable regions of the network with and . From the tables, we can see that the proposed model’s performance remains remarkable with different node densities as compared to SEED, CEEC, ABC, and ZBR.

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.