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Well-Suited Similarity Functions for Data Aggregation in Cluster-Based Underwater Wireless Sensor Networks
Joint Authors
Oh, Seung-Hyun
Tran, Khoa Thi-Minh
Byun, Jeong-Yong
Source
International Journal of Distributed Sensor Networks
Issue
Vol. 2013, Issue - (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-08-07
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Telecommunications Engineering
Information Technology and Computer Science
Abstract EN
This paper presents an efficient data aggregation approach for cluster-based underwater wireless sensor networks in order to prolong network lifetime.
In data aggregation, an aggregator collects sensed data from surrounding nodes and transmits the aggregated data to a base station.
The major goal of data aggregation is to minimize data redundancy, ensuring high data accuracy and reducing the aggregator’s energy consumption.
Hence, similarity functions could be useful as a part of the data aggregation process for resolving inconsistencies in collected data.
Our approach is to determine and apply well-suited similarity functions for cluster-based underwater wireless sensor networks.
In this paper, we show the effectiveness of similarity functions, especially the Euclidean distance and cosine distance, in reducing the packet size and minimizing the data redundancy of cluster-based underwater wireless sensor networks.
Our results show that the Euclidean distance and cosine distance increase the efficiency of the network both in theory and simulation.
American Psychological Association (APA)
Tran, Khoa Thi-Minh& Oh, Seung-Hyun& Byun, Jeong-Yong. 2013. Well-Suited Similarity Functions for Data Aggregation in Cluster-Based Underwater Wireless Sensor Networks. International Journal of Distributed Sensor Networks،Vol. 2013, no. -, pp.1-7.
https://search.emarefa.net/detail/BIM-487765
Modern Language Association (MLA)
Tran, Khoa Thi-Minh…[et al.]. Well-Suited Similarity Functions for Data Aggregation in Cluster-Based Underwater Wireless Sensor Networks. International Journal of Distributed Sensor Networks Vol. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-487765
American Medical Association (AMA)
Tran, Khoa Thi-Minh& Oh, Seung-Hyun& Byun, Jeong-Yong. Well-Suited Similarity Functions for Data Aggregation in Cluster-Based Underwater Wireless Sensor Networks. International Journal of Distributed Sensor Networks. 2013. Vol. 2013, no. -, pp.1-7.
https://search.emarefa.net/detail/BIM-487765
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-487765