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Semitensor Product Compressive Sensing for Big Data Transmission in Wireless Sensor Networks
Joint Authors
Peng, Haipeng
Kurths, Jürgen
Tian, Ye
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-03-22
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Big data transmission in wireless sensor network (WSN) consumes energy while the node in WSN is energy-limited, and the data transmitted needs to be encrypted resulting from the ease of being eavesdropped in WSN links.
Compressive sensing (CS) can encrypt data and reduce the data volume to solve these two problems.
However, the nodes in WSNs are not only energy-limited, but also storage and calculation resource-constrained.
The traditional CS uses the measurement matrix as the secret key, which consumes a huge storage space.
Moreover, the calculation cost of the traditional CS is large.
In this paper, semitensor product compressive sensing (STP-CS) is proposed, which reduces the size of the secret key to save the storage space by breaking through the dimension match restriction of the matrix multiplication and decreases the calculation amount to save the calculation resource.
Simulation results show that STP-CS encryption can achieve better performances of saving storage and calculation resources compared with the traditional CS encryption.
American Psychological Association (APA)
Peng, Haipeng& Tian, Ye& Kurths, Jürgen. 2017. Semitensor Product Compressive Sensing for Big Data Transmission in Wireless Sensor Networks. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1192216
Modern Language Association (MLA)
Peng, Haipeng…[et al.]. Semitensor Product Compressive Sensing for Big Data Transmission in Wireless Sensor Networks. Mathematical Problems in Engineering No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1192216
American Medical Association (AMA)
Peng, Haipeng& Tian, Ye& Kurths, Jürgen. Semitensor Product Compressive Sensing for Big Data Transmission in Wireless Sensor Networks. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1192216
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1192216