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Wireless Meter Reading Based Energy-Balanced Steady Clustering Routing Algorithm for Sensor NetworksTIAN, Y. , TANG, Z. |
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Author keywords
energy-balanced, energy-distance function, steady clustering, wireless sensor networks
References keywords
networks(18), sensor(15), energy(8), distributed(8), data(7), computing(5), parallel(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2011-05-30
Volume 11, Issue 2, Year 2011, On page(s): 9 - 14
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2011.02002
Web of Science Accession Number: 000293840500002
SCOPUS ID: 79958824204
Abstract
According to the characteristics of wireless meter reading system, an energy-balanced and energy-efficient steady clustering routing algorithm (EBSC, Energy-Balanced Steady Clustering) is proposed. In the clustering mechanism, the current cluster head nodes determine cluster head nodes for next round according to the residual energy of the cluster members. In the next round, each non-cluster head node decides the cluster to which it will belong according to energy-distance function. The cluster head nodes send data to base station by the communication model of single hop and multi-hop that is decided according to the criterion of minimum energy consumption. In EBSC algorithm, the number of cluster head nodes generated in each round is very steady, and EBSC combines the advantage both distributed and centralized clustering algorithm. Experimental results show that the proposed routing algorithm not only efficiently uses limited energy of network nodes, but also well balances energy consumption of all nodes, and significantly prolongs network lifetime. |
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[1] A Real-Time Big Data Gathering Algorithm Based on Indoor Wireless Sensor Networks for Risk Analysis of Industrial Operations, Ding, Xuejun, Tian, Yong, Yu, Yan, IEEE Transactions on Industrial Informatics, ISSN 1551-3203, Issue 3, Volume 12, 2016.
Digital Object Identifier: 10.1109/TII.2015.2436337 [CrossRef]
[2] Energy-efficient clustering method for wireless sensor networks using modified gravitational search algorithm, Ebrahimi Mood, Sepehr, Javidi, Mohammad Masoud, Evolving Systems, ISSN 1868-6478, Issue 4, Volume 11, 2020.
Digital Object Identifier: 10.1007/s12530-019-09264-x [CrossRef]
[3] Third-Order Channel Propagation Model-Based Indoor Adaptive Localization Algorithm for Wireless Sensor Networks, Tian, Yong, Tang, Zhenan, Yu, Yan, IEEE Antennas and Wireless Propagation Letters, ISSN 1536-1225, Issue , 2013.
Digital Object Identifier: 10.1109/LAWP.2013.2293578 [CrossRef]
[4] THWSN: Enhanced Energy-Efficient Clustering Approach for Three-Tier Heterogeneous Wireless Sensor Networks, Kumar, Nitin, Rani, Preeti, Kumar, Vinod, Athawale, Shashikant V., Koundal, Deepika, IEEE Sensors Journal, ISSN 1530-437X, Issue 20, Volume 22, 2022.
Digital Object Identifier: 10.1109/JSEN.2022.3200597 [CrossRef]
[5] Wireless sensor location systems comparative performances evaluation, Coca, Eugen, Popa, Valentin, 2012 IEEE 18th International Symposium for Design and Technology in Electronic Packaging (SIITME), ISBN 978-1-4673-4760-0, 2012.
Digital Object Identifier: 10.1109/SIITME.2012.6384398 [CrossRef]
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Stefan cel Mare University of Suceava, Romania
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