A k-means-based formation algorithm for the delay-aware data collection network structure

Pat Yam Tsoi; Chi Tsun Cheng; Nuwan Ganganath

doi:10.1109/CyberC.2014.73

A k-means-based formation algorithm for the delay-aware data collection network structure

Pat Yam Tsoi, Chi Tsun Cheng, Nuwan Ganganath

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

Abstract

A wireless sensor network (WSN) consists of a large number of wireless sensor nodes that collect information from their sensing terrain. Wireless sensor nodes are, in general, battery-powered devices with limited processing and transmission power. Therefore, the lifetime of WSNs heavily depends on their energy efficiency. Multiple-cluster 2-hop (MC2H) network structure is commonly used in WSNs to reduce energy consumption due to long-range communications. However, networks with the MC2H network structure are commonly associated with long data collection processes. The delay-aware data collection network structure (DADCNS) is proposed to shorten the duration of data collection processes without sacrificing network lifetime. In this paper, a k-means-based formation algorithm for the DADCNS, namely DADCNS-RK, is proposed. The proposed algorithm can organize a network into the DADCNS, while minimizing the total communication distance among connected sensor nodes by performing k-means clustering recursively. Simulation results show that, when comparing with other DADCNSs formed by different algorithms, the proposed algorithm can reduce the total communication distances of networks significantly.

Original language	English
Title of host publication	Proceedings - 2014 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2014
Publisher	IEEE
Pages	384-388
Number of pages	5
ISBN (Electronic)	9781479962358
DOIs	https://doi.org/10.1109/CyberC.2014.73
Publication status	Published - 1 Jan 2014
Event	6th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2014 - Shanghai, China Duration: 10 Oct 2014 → 12 Oct 2014

Conference

Conference	6th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2014
Country/Territory	China
City	Shanghai
Period	10/10/14 → 12/10/14

Keywords

data collection process
delay-aware
k-means algorithms
resources management
wireless sensor networks

ASJC Scopus subject areas

Computational Theory and Mathematics
Computer Science Applications
Software

More information

10.1109/CyberC.2014.73

http://hdl.handle.net/10397/53654

Cite this

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title = "A k-means-based formation algorithm for the delay-aware data collection network structure",

abstract = "A wireless sensor network (WSN) consists of a large number of wireless sensor nodes that collect information from their sensing terrain. Wireless sensor nodes are, in general, battery-powered devices with limited processing and transmission power. Therefore, the lifetime of WSNs heavily depends on their energy efficiency. Multiple-cluster 2-hop (MC2H) network structure is commonly used in WSNs to reduce energy consumption due to long-range communications. However, networks with the MC2H network structure are commonly associated with long data collection processes. The delay-aware data collection network structure (DADCNS) is proposed to shorten the duration of data collection processes without sacrificing network lifetime. In this paper, a k-means-based formation algorithm for the DADCNS, namely DADCNS-RK, is proposed. The proposed algorithm can organize a network into the DADCNS, while minimizing the total communication distance among connected sensor nodes by performing k-means clustering recursively. Simulation results show that, when comparing with other DADCNSs formed by different algorithms, the proposed algorithm can reduce the total communication distances of networks significantly.",

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Tsoi, PY, Cheng, CT & Ganganath, N 2014, A k-means-based formation algorithm for the delay-aware data collection network structure. in Proceedings - 2014 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2014., 6984337, IEEE, pp. 384-388, 6th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2014, Shanghai, China, 10/10/14. https://doi.org/10.1109/CyberC.2014.73

A k-means-based formation algorithm for the delay-aware data collection network structure. / Tsoi, Pat Yam; Cheng, Chi Tsun; Ganganath, Nuwan.
Proceedings - 2014 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2014. IEEE, 2014. p. 384-388 6984337.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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N2 - A wireless sensor network (WSN) consists of a large number of wireless sensor nodes that collect information from their sensing terrain. Wireless sensor nodes are, in general, battery-powered devices with limited processing and transmission power. Therefore, the lifetime of WSNs heavily depends on their energy efficiency. Multiple-cluster 2-hop (MC2H) network structure is commonly used in WSNs to reduce energy consumption due to long-range communications. However, networks with the MC2H network structure are commonly associated with long data collection processes. The delay-aware data collection network structure (DADCNS) is proposed to shorten the duration of data collection processes without sacrificing network lifetime. In this paper, a k-means-based formation algorithm for the DADCNS, namely DADCNS-RK, is proposed. The proposed algorithm can organize a network into the DADCNS, while minimizing the total communication distance among connected sensor nodes by performing k-means clustering recursively. Simulation results show that, when comparing with other DADCNSs formed by different algorithms, the proposed algorithm can reduce the total communication distances of networks significantly.

AB - A wireless sensor network (WSN) consists of a large number of wireless sensor nodes that collect information from their sensing terrain. Wireless sensor nodes are, in general, battery-powered devices with limited processing and transmission power. Therefore, the lifetime of WSNs heavily depends on their energy efficiency. Multiple-cluster 2-hop (MC2H) network structure is commonly used in WSNs to reduce energy consumption due to long-range communications. However, networks with the MC2H network structure are commonly associated with long data collection processes. The delay-aware data collection network structure (DADCNS) is proposed to shorten the duration of data collection processes without sacrificing network lifetime. In this paper, a k-means-based formation algorithm for the DADCNS, namely DADCNS-RK, is proposed. The proposed algorithm can organize a network into the DADCNS, while minimizing the total communication distance among connected sensor nodes by performing k-means clustering recursively. Simulation results show that, when comparing with other DADCNSs formed by different algorithms, the proposed algorithm can reduce the total communication distances of networks significantly.

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A k-means-based formation algorithm for the delay-aware data collection network structure

Abstract

Conference

Keywords

ASJC Scopus subject areas

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