Dynamic cluster header selection and conditional re-clustering for wireless sensor networks

Baek, Jinsuk; An, Sun Kyong; Fisher, Paul S.

doi:10.1109/tce.2010.5681097

Cited by 27 publications

(13 citation statements)

References 10 publications

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“…For example, network is first partitioned into clusters and then CH is selected for each cluster [14] [15]. Another way of clustering is select the CH first and then remaining nodes will join CH to form a cluster [4] [9] [16].…”

Section: A Clustering Strategymentioning

confidence: 99%

Energy Efficient Clustering Protocol for Wireless Sensor Network

Agrawal¹,

Pandey²,

Motwani³

2017

IJET

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Abstract-Energy consumption of sensor nodes in wireless sensor networks (WSNs) is a big challenge for improving network lifetime. Several approaches have been proposed in existing literature for this. One of the best approach can be considered as clustering. During clustering strategy, cluster head (CH) selection plays an important role because CH is responsible for collecting data from the member nodes, processing and forwarding the data to next level or sink. Because of this, energy requirement for CH is more than member nodes. In our work we have tried to minimize energy consumption of a network by selecting optimal CH in WSNs using energy and distance parameters. In this paper we propose CH selection algorithm using energy and distance (E/D) parameter based on fan-shaped design. Experimental results prove that our method has advantages of selecting CH over random CH selection method. Clustering divides the network into smaller partitions. Each partition is known as cluster. Each cluster selects a CH which is responsible for collecting data from member nodes and forwarding it to the next cluster or sink during clustering process. Keyword-Wireless SensorCH is a node which consumes more power than member nodes. Hence it should be selected optimally to improve the network performance. Cluster based technique in wireless sensor network employees two types of communication namely intra-cluster communication and inter-cluster communication. In intra-cluster communication the member nodes of a cluster selects a CH and send data to it. During inter-cluster communication one CH will send the aggregated data of a cluster to another CH.In our work we have focused on effective communication strategy to select best CH so that energy spent in communication should be minimized resulting into optimal network utilization. Our work is based on the fanshaped clustering model proposed by Hai Lin et.al [1]. The whole network is divided into fan-shaped clusters in which sink occupies the center position.In this paper we optimize the CH selection procedure by considering following two parameters based on fan shaped architecture. 1. Energy of a node and 2. Distance of a node from sinkThe remainder of this paper is organized as follows: Section 2 describes the clustering technique and its related works. Section 3 describes our E/D approach in detail specifically the CH selection formula. Section 4

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Section: A Clustering Strategymentioning

confidence: 99%

Energy Efficient Clustering Protocol for Wireless Sensor Network

Agrawal¹,

Pandey²,

Motwani³

2017

IJET

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“…In order to rotate the load-intensive CH role, nodes periodically perform re-clustering operations at each re-clustering stage to elect a new set of CHs that will serve the network during the next round. Recently, some studies have emphasized the need for a fully asynchronous operation in a self-organized WSN, which does not require time rounds [2] [3] [4]. These asynchronous node clustering protocols are designed for networks with single hops from CHs to the data sink and are not applicable to multihop WSNs, since in such networks it is essential to consider the multihop traffic loads.…”

Section: Related Workmentioning

confidence: 99%

“…However, protocols based on time-rounds require network-wide time synchronisation, so that nodes can simultaneously engage in this short reclustering phase and perform cooperative operations to elect the new set of CHs. Some recent studies [2] [3] [4] propose asynchronous clustering to avoid this requirement, however the proposed protocols assume direct links from CHs to the data sink, and therefore are limited to scenarios in which sensors can reach the sink in a single hop.…”

Section: Introductionmentioning

confidence: 99%

“…Sensor nodes dynamically change their transmission ranges to effectively modify the network hierarchy, considering residual node energy levels as well as the unbalanced traffic loads on CHs caused by multihop packet forwarding. In contrast to existing clustering protocols proposed for multihop WSNs, ACP does not require network-wide timesynchronisation [2] [5] [6] [7], estimation of inter-node distances [6], specific network topologies [7], or static estimations of energy consumption levels over multihop paths [7]. ACP is compared with the Unequal Cluster-based Routing (UCR) protocol in multihop WSNs in terms of gains in average throughput at the data sink and network lifetime.…”

Section: Introductionmentioning

confidence: 99%

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Asynchronous clustering of multihop Wireless Sensor Networks

Vural

Navaratnam

Wang

et al. 2014

2014 IEEE International Conference on Communications (ICC)

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Abstract-Node clustering has been widely studied in recent years for Wireless Sensor Networks (WSN) as a technique to form a hierarchical structure and prolong network lifetime by reducing the number of packet transmissions. Cluster Heads (CH) are elected in a distributed way among sensors, but are often highly overloaded, and therefore re-clustering operations should be performed to share the resource intensive CH-role. Existing protocols involve periodic network-wide re-clustering operations that are simultaneously performed, which requires global time synchronisation. To address this issue, some recent studies have proposed asynchronous node clustering for networks with direct links from CHs to the data sink. However, for large-scale WSNs, multihop packet delivery to the sink is required since longrange transmissions are costly for sensor nodes. In this paper, we present an asynchronous node clustering protocol designed for multihop WSNs, considering dynamic conditions such as residual node energy levels and unbalanced data traffic loads caused by packet forwarding. Simulation results demonstrate that it is possible to achieve similar levels of lifetime extension by reclustering a multihop WSN via independently made decisions at CHs, without a need for time synchronisation required by existing synchronous protocols.

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“…Whether for IP backbone network, cellar mobile network or Ad-hoc network, the simple graph theory is the main tool for research on architecture control [8][9][10][11] and counting routing protocols [3,4,[12][13][14]. But in large-scale wireless self-organized sensor networks, the number of sensor nodes can be hundreds or thousands of times of that of backbone network or mobile network.…”

Section: Hypergraph Model For Wireless Self-organized Sensor Networkmentioning

confidence: 99%

An Energy-Efficient and Fault-Tolerant Convergecast Protocol in Wireless Sensor Networks

Yang

Kang

Nan

2012

International Journal of Distributed Sensor Networks

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The simple graph theory is commonly employed in wireless sensor networks topology control. An inherent problem of smallgranularity algorithms is the high computing complexity and large solution space when managing large-scale WSNs. Computed transmission paths are of low fault tolerance because of unattended sensor nodes and frail wireless transmitting channels. This paper uses hyper-graph theory to solve these practical problems and proposes a spanning hyper-tree algorithm (SHTa) to compute the minimum transmitting power delivery paths set for WSNs convergecast. There are three main contributions of this paper: (1) we present a novel hyper-graph model to abstract large-scale and high connectivity WSNs into a robust hyper-tree infrastructure; (2) we present a precise mathematical derivation that solves the "hyper-tree existence" problem; (3) SHTa is proposed to compute the delivery paths set, which is the minimum power transmitting convergecast hyper-tree. Variable scale hyper-edges represented as computing units limit solution space and reduce computing complexity. Mutual backup delivery paths in one hyper-edge improve the capability of fault tolerance. With experiment results, SHTa computes short latency paths with low energy consumption, compared with previous algorithms. Furthermore, in dynamic experiments scenes, SHTa retains its robust transmitting quality and presents high fault tolerance.

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Dynamic cluster header selection and conditional re-clustering for wireless sensor networks

Cited by 27 publications

References 10 publications

Energy Efficient Clustering Protocol for Wireless Sensor Network

Energy Efficient Clustering Protocol for Wireless Sensor Network

Asynchronous clustering of multihop Wireless Sensor Networks

An Energy-Efficient and Fault-Tolerant Convergecast Protocol in Wireless Sensor Networks

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