Pattern-based matrix-size optimization algorithm for compressive sensing in real-world wireless sensor networks

Akito Ito; Naoya Namatame; Jin Nakazawa; Hideyuki Tokuda

doi:10.1145/2426656.2426705

Pattern-based matrix-size optimization algorithm for compressive sensing in real-world wireless sensor networks

Akito Ito, Naoya Namatame, Jin Nakazawa, Hideyuki Tokuda

Faculty of Environment and Information Studies

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Compressive Sensing (CS) is a novel approach for data representation, which can represent signals at a rate below the Nyquist rate with low computation costs on encoder. For these characteristics, CS is very suitable for low power sensor nodes to save power consumption that is a primary problem inWireless Sensor Networks (WSN). But there are many problems when using CS in a real environment. One of these is that pattern of sensor values change dynamically. It decreases the efficiency of power consumption and accuracy of recovery. To solve the problem, we propose Pattern-based Matrix-size Optimization Algorithm (PMOA), which aims to improve the accuracy of exact recovery and power consumption.

Original language	English
Title of host publication	SenSys 2012 - Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems
Pages	355-356
Number of pages	2
DOIs	https://doi.org/10.1145/2426656.2426705
Publication status	Published - 2012
Event	10th ACM Conference on Embedded Networked Sensor Systems, SenSys 2012 - Toronto, ON, Canada Duration: 2012 Nov 6 → 2012 Nov 9

Publication series

Name	SenSys 2012 - Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems

Other

Other	10th ACM Conference on Embedded Networked Sensor Systems, SenSys 2012
Country/Territory	Canada
City	Toronto, ON
Period	12/11/6 → 12/11/9

Keywords

Compressive sensing
Information processing

ASJC Scopus subject areas

Computer Networks and Communications

Access to Document

10.1145/2426656.2426705

Cite this

Ito, A., Namatame, N., Nakazawa, J., & Tokuda, H. (2012). Pattern-based matrix-size optimization algorithm for compressive sensing in real-world wireless sensor networks. In SenSys 2012 - Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems (pp. 355-356). (SenSys 2012 - Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems). https://doi.org/10.1145/2426656.2426705

Pattern-based matrix-size optimization algorithm for compressive sensing in real-world wireless sensor networks. / Ito, Akito; Namatame, Naoya; Nakazawa, Jin et al.
SenSys 2012 - Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems. 2012. p. 355-356 (SenSys 2012 - Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ito, A, Namatame, N, Nakazawa, J & Tokuda, H 2012, Pattern-based matrix-size optimization algorithm for compressive sensing in real-world wireless sensor networks. in SenSys 2012 - Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems. SenSys 2012 - Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems, pp. 355-356, 10th ACM Conference on Embedded Networked Sensor Systems, SenSys 2012, Toronto, ON, Canada, 12/11/6. https://doi.org/10.1145/2426656.2426705

Ito A, Namatame N, Nakazawa J, Tokuda H. Pattern-based matrix-size optimization algorithm for compressive sensing in real-world wireless sensor networks. In SenSys 2012 - Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems. 2012. p. 355-356. (SenSys 2012 - Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems). doi: 10.1145/2426656.2426705

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Pattern-based matrix-size optimization algorithm for compressive sensing in real-world wireless sensor networks

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