Energy-based clustering for wireless sensor network lifetime optimization

Ducrocq, Thierry; Mitton, Nathalie; Hauspie, Michaël

doi:10.1109/wcnc.2013.6554695

Cited by 21 publications

(17 citation statements)

References 15 publications

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“…It aims at increasing the lifetime, thus keeping all the nodes alive to perform a specific task. Simulation results proved that BLAC increases the full network lifetime by three times than the traditional clustering schemes through balancing energy consumption of nodes and it gives high data ratio [17]. BLAC has four variants; BLACbg uses battery level and degree of a node; BLAC-bs combines the battery level and density of a node.…”

Section: Battery Level Aware Clustering(blac)mentioning

confidence: 98%

Recent Trends in Energy-efficient Clustering in WSNs

Islam¹,

Kumar²,

Maheshwari³

et al. 2014

IJCA

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Tremendous growth has been observed in the use of Wireless sensor networks (WSNs) in the last decade. WSNs behave like an interface between the virtual and physical worlds. Sensor nodes sense the changes in external environment and send the data to other nodes in the network or the sink, also called Base Station (BS). The performance of the network gets affected due to limited battery lifetime of sensor nodes. Many clustering and power management protocols have been specifically designed for WSN to reduce energy consumption. Improvements are being made day by day in the basic clustering protocols. In this paper, a survey of the recent clustering protocols in WSNs has been presented and a comparison has been done of various protocols.

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Section: Battery Level Aware Clustering(blac)mentioning

confidence: 98%

Recent Trends in Energy-efficient Clustering in WSNs

Islam¹,

Kumar²,

Maheshwari³

et al. 2014

IJCA

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show abstract

“…Other solutions, such as energy-based clustering for WSNs lifetime optimization and balancing energy consumption in clustered WSNs (BLAC), were proposed by Ducrocq et al [23]. BLAC used the energy level and the degree of nodes or the density of nodes for clustering.…”

Section: Literature Reviewmentioning

confidence: 99%

A Hybrid Unequal Clustering Based on Density with Energy Conservation in Wireless Nodes

et al. 2019

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The Internet of things (IoT) provides the possibility of communication between smart devices and any object at any time. In this context, wireless nodes play an important role in reducing costs and simple use. Since these nodes are often used in less accessible locations, recharging their battery is hardly feasible and in some cases is practically impossible. Hence, energy conservation within each node is a challenging discussion. Clustering is an efficient solution to increase the lifetime of the network and reduce the energy consumption of the nodes. In this paper, a novel hybrid unequal multi-hop clustering based on density (HCD) is proposed to increase the network lifetime. In the proposed protocol, the cluster head (CH) selection is performed only by comparing the status of each node to its neighboring nodes. In this new technique, the parameters involving energy of nodes, the number of neighboring nodes, the distance to the base station (BS), and the layer where the node is placed in are considered in CH selection. So, in this new and simple technique considers energy consumption of the network and load balancing. Clustering is performed unequally so that cluster heads (CHs) close to BS have more energy for data relay. Also, a hybrid dynamic–static clustering was performed to decrease overhead. In the current protocol, a distributed clustering and multi-hop routing approach was applied between cluster members (CMs), to CHs, and CHs to BS. HCD is applied as a novel assistance to cluster heads (ACHs) mechanism, in a way that a CH accepts to use member nodes with suitable state to share traffic load. Furthermore, we performed simulation for two different scenarios. Simulation results showed the reliability of the proposed method as it was resulted in a significant increase in network stability and energy balance as well as network lifetime and efficiency.

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“…Simulation results demonstrate that the ACT protocol reduces the energy consumption of the CHs near the sink efficiently. Ducrocq et al [8] presented the battery-level-aware clustering (BLAC) scheme that considers combining the battery level and another metric for electing the CHs. The objective of this work is to maximize the lifetime of all nodes for satisfying the application needs.…”

Section: Literature Reviewmentioning

confidence: 99%

“…It is evaluated using (8). We consider network lifetime as defined in Section III-F. Further, we define two network performance parameters mentioned earlier as follows.…”

Section: ) Energy Consumption Rate Per Ch In a Layer (Ecr Permentioning

confidence: 99%

Lifetime Optimizing Clustering Structure Using Archimedes’ Spiral-Based Deployment in WSNs

Ghosal¹,

Halder²

2017

IEEE Systems Journal

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In wireless sensor networks (WSNs), preserving energy requires utmost attention, as they are highly resource constrained. Clustering is commonly considered as one of the efficient energy conservation techniques. In a clustered WSN, due to the nature of operation, cluster heads (CHs) near the sink bear the major share of data forwarding compared with the CHs far away from the sink, resulting in an energy hole problem. First, we have analyzed the optimization of network lifetime by balancing the energy consumption among different CHs. To meet the requirement of optimization of network lifetime, we have devised a routing-aware optimal clustering strategy. Further, keeping the network model in mind, we identify Archimedes' spiral, based on which a deployment function is proposed for distributing a member node and a CH. The performance of the optimal clustering strategy is evaluated in terms of energy balance and network lifetime. Simulation results show that our scheme provides satisfactory network performance in terms of end-to-end delay and throughput. Finally, all the results are compared with two competing schemes that confirm our scheme's supremacy in terms of both design performance metrics as well as network performance metrics.Index Terms-Clustering, energy balance, network lifetime, node deployment, wireless sensor network.

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Energy-based clustering for wireless sensor network lifetime optimization

Cited by 21 publications

References 15 publications

Recent Trends in Energy-efficient Clustering in WSNs

Recent Trends in Energy-efficient Clustering in WSNs

A Hybrid Unequal Clustering Based on Density with Energy Conservation in Wireless Nodes

Lifetime Optimizing Clustering Structure Using Archimedes’ Spiral-Based Deployment in WSNs

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