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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.


(a) The complete description of phases in a round of model-based optimal cluster heads (MOCHs) and the association process of non-cluster member for data forwarding; (b) CH data collection during a round in slots.
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sensors-17-00440-f008: (a) The complete description of phases in a round of model-based optimal cluster heads (MOCHs) and the association process of non-cluster member for data forwarding; (b) CH data collection during a round in slots.

Mentions: Some sensor nodes in the network are not receiving a CH advertisement message from any CH. These nodes wait for a specific time slot for the CH advertisement message and after that predefined time slot, these nodes start sending their data directly to the BS. In the literature of WSN [7,8,9,10,11], these self-generated CHs are known as . These self-generated force CHs are a waste of system resources, because all the time in a round these force CHs repeatedly send their information to the BS which affects the network stability. We also define a strategy to deal with these force CHs and we named them Non-Associated Cluster Members (NACM). In MOCHs, if a node does not receive any CH advertisement message, it will send a data forwarding request to the CH of its closest neighbor node. The requested CH will assign a data slot for this node at the request. Then the neighbor node will forward the data of this node during the assigned slot as shown Figure 8. The energy consumption of a node to forward a data packet of l bits is:(22)ENACM=2lEelec+lεfsd(N,NBR)2


Markov Chain Model-Based Optimal Cluster Heads Selection for Wireless Sensor Networks
(a) The complete description of phases in a round of model-based optimal cluster heads (MOCHs) and the association process of non-cluster member for data forwarding; (b) CH data collection during a round in slots.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

sensors-17-00440-f008: (a) The complete description of phases in a round of model-based optimal cluster heads (MOCHs) and the association process of non-cluster member for data forwarding; (b) CH data collection during a round in slots.
Mentions: Some sensor nodes in the network are not receiving a CH advertisement message from any CH. These nodes wait for a specific time slot for the CH advertisement message and after that predefined time slot, these nodes start sending their data directly to the BS. In the literature of WSN [7,8,9,10,11], these self-generated CHs are known as . These self-generated force CHs are a waste of system resources, because all the time in a round these force CHs repeatedly send their information to the BS which affects the network stability. We also define a strategy to deal with these force CHs and we named them Non-Associated Cluster Members (NACM). In MOCHs, if a node does not receive any CH advertisement message, it will send a data forwarding request to the CH of its closest neighbor node. The requested CH will assign a data slot for this node at the request. Then the neighbor node will forward the data of this node during the assigned slot as shown Figure 8. The energy consumption of a node to forward a data packet of l bits is:(22)ENACM=2lEelec+lεfsd(N,NBR)2

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.