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 |
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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 | |
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 |
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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