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A survey on clustering routing protocols in wireless sensor networks.

Liu X - Sensors (Basel) (2012)

Bottom Line: Owing to a variety of advantages, clustering is becoming an active branch of routing technology in WSNs.In particular, we systematically analyze a few prominent WSN clustering routing protocols and compare these different approaches according to our taxonomy and several significant metrics.Finally, we summarize and conclude the paper with some future directions.

View Article: PubMed Central - PubMed

Affiliation: School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510641, China. liuxuxun@scut.edu.cn

ABSTRACT
The past few years have witnessed increased interest in the potential use of wireless sensor networks (WSNs) in a wide range of applications and it has become a hot research area. Based on network structure, routing protocols in WSNs can be divided into two categories: flat routing and hierarchical or clustering routing. Owing to a variety of advantages, clustering is becoming an active branch of routing technology in WSNs. In this paper, we present a comprehensive and fine grained survey on clustering routing protocols proposed in the literature for WSNs. We outline the advantages and objectives of clustering for WSNs, and develop a novel taxonomy of WSN clustering routing methods based on complete and detailed clustering attributes. In particular, we systematically analyze a few prominent WSN clustering routing protocols and compare these different approaches according to our taxonomy and several significant metrics. Finally, we summarize and conclude the paper with some future directions.

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Illustration of the Geographical Clustering in PANEL.
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f4-sensors-12-11113: Illustration of the Geographical Clustering in PANEL.

Mentions: PANEL assumes that the nodes are deployed in a bounded area, which is partitioned into geographical clusters. The clustering is determined before the deployment of the network, and each node is pre-loaded with the geographical information of the cluster to which it belongs. PANEL introduces a notion of reference point. At the beginning of each epoch, a reference point Rj is computed in each cluster j by the nodes in a distributed manner in terms of the epoch number, as follows:(4)R→j=Q→j+Q→where Q⃗j is the position of the lower-left corner of cluster j. Furthermore, the current epoch number e is known by every node and the computation consists in calling a pseudo-random function H(e) that maps e to a relative position Q⃗ nside the cluster, i.e.,:(5)H(e)=Q→where Q⃗ ∈ (−δd, d + δd) × (−δd, d + δd), d is the size of the cluster, and δ < 1 is a parameter which expresses the magnitude of this re-sizing operation in percent of the original cluster size d. Once the reference point is computed, the node that is the closest to the reference point will be elected the CH for the given epoch. The reference points of the clusters will be re-computed and the CH election procedure will be re-executed in next epochs. This CH election procedure ensures load balancing in PANEL because each node of the cluster can become CH with almost the same probability. The illustration of the geographical clustering in PANEL is shown in Figure 4.


A survey on clustering routing protocols in wireless sensor networks.

Liu X - Sensors (Basel) (2012)

Illustration of the Geographical Clustering in PANEL.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3472877&req=5

f4-sensors-12-11113: Illustration of the Geographical Clustering in PANEL.
Mentions: PANEL assumes that the nodes are deployed in a bounded area, which is partitioned into geographical clusters. The clustering is determined before the deployment of the network, and each node is pre-loaded with the geographical information of the cluster to which it belongs. PANEL introduces a notion of reference point. At the beginning of each epoch, a reference point Rj is computed in each cluster j by the nodes in a distributed manner in terms of the epoch number, as follows:(4)R→j=Q→j+Q→where Q⃗j is the position of the lower-left corner of cluster j. Furthermore, the current epoch number e is known by every node and the computation consists in calling a pseudo-random function H(e) that maps e to a relative position Q⃗ nside the cluster, i.e.,:(5)H(e)=Q→where Q⃗ ∈ (−δd, d + δd) × (−δd, d + δd), d is the size of the cluster, and δ < 1 is a parameter which expresses the magnitude of this re-sizing operation in percent of the original cluster size d. Once the reference point is computed, the node that is the closest to the reference point will be elected the CH for the given epoch. The reference points of the clusters will be re-computed and the CH election procedure will be re-executed in next epochs. This CH election procedure ensures load balancing in PANEL because each node of the cluster can become CH with almost the same probability. The illustration of the geographical clustering in PANEL is shown in Figure 4.

Bottom Line: Owing to a variety of advantages, clustering is becoming an active branch of routing technology in WSNs.In particular, we systematically analyze a few prominent WSN clustering routing protocols and compare these different approaches according to our taxonomy and several significant metrics.Finally, we summarize and conclude the paper with some future directions.

View Article: PubMed Central - PubMed

Affiliation: School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510641, China. liuxuxun@scut.edu.cn

ABSTRACT
The past few years have witnessed increased interest in the potential use of wireless sensor networks (WSNs) in a wide range of applications and it has become a hot research area. Based on network structure, routing protocols in WSNs can be divided into two categories: flat routing and hierarchical or clustering routing. Owing to a variety of advantages, clustering is becoming an active branch of routing technology in WSNs. In this paper, we present a comprehensive and fine grained survey on clustering routing protocols proposed in the literature for WSNs. We outline the advantages and objectives of clustering for WSNs, and develop a novel taxonomy of WSN clustering routing methods based on complete and detailed clustering attributes. In particular, we systematically analyze a few prominent WSN clustering routing protocols and compare these different approaches according to our taxonomy and several significant metrics. Finally, we summarize and conclude the paper with some future directions.

Show MeSH