IEICE TRANSACTIONS on Communications
Low-Complexity and Energy-Efficient Algorithms on Image Compression for Wireless Sensor Networks
Summary :
This paper proposes two algorithms to balance energy consumption among sensor nodes by distributing the workload of image compression tasks within a cluster on wireless sensor networks. The main point of the proposed algorithms is to adopt the energy threshold, which is used when we implement the exchange and/or assignment of tasks among sensor nodes. The threshold is well adaptive to the residual energy of sensor nodes, input image, compressed output, and network parameters. We apply the lapped transform technique, an extended version of the discrete cosine transform, and run length encoding before Lempel-Ziv-Welch coding to the proposed algorithms to improve both quality and compression rate in image compression scheme. We extensively conduct computational experiments to verify the our methods and find that the proposed algorithms achieve not only balancing the total energy consumption among sensor nodes and, thus, increasing the overall network lifetime, but also reducing block noise in image compression.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E93-B No.12 pp.3438-3447
- Publication Date
- 2010/12/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.E93.B.3438
- Type of Manuscript
- Special Section PAPER (Special Section on Wireless Distributed Networks)
- Category
Authors
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Phat NGUYEN HUU, Vinh TRAN-QUANG, Takumi MIYOSHI, "Low-Complexity and Energy-Efficient Algorithms on Image Compression for Wireless Sensor Networks" in IEICE TRANSACTIONS on Communications,
vol. E93-B, no. 12, pp. 3438-3447, December 2010, doi: 10.1587/transcom.E93.B.3438.
Abstract: This paper proposes two algorithms to balance energy consumption among sensor nodes by distributing the workload of image compression tasks within a cluster on wireless sensor networks. The main point of the proposed algorithms is to adopt the energy threshold, which is used when we implement the exchange and/or assignment of tasks among sensor nodes. The threshold is well adaptive to the residual energy of sensor nodes, input image, compressed output, and network parameters. We apply the lapped transform technique, an extended version of the discrete cosine transform, and run length encoding before Lempel-Ziv-Welch coding to the proposed algorithms to improve both quality and compression rate in image compression scheme. We extensively conduct computational experiments to verify the our methods and find that the proposed algorithms achieve not only balancing the total energy consumption among sensor nodes and, thus, increasing the overall network lifetime, but also reducing block noise in image compression.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E93.B.3438/_p
Copy
@ARTICLE{e93-b_12_3438,
author={Phat NGUYEN HUU, Vinh TRAN-QUANG, Takumi MIYOSHI, },
journal={IEICE TRANSACTIONS on Communications},
title={Low-Complexity and Energy-Efficient Algorithms on Image Compression for Wireless Sensor Networks},
year={2010},
volume={E93-B},
number={12},
pages={3438-3447},
abstract={This paper proposes two algorithms to balance energy consumption among sensor nodes by distributing the workload of image compression tasks within a cluster on wireless sensor networks. The main point of the proposed algorithms is to adopt the energy threshold, which is used when we implement the exchange and/or assignment of tasks among sensor nodes. The threshold is well adaptive to the residual energy of sensor nodes, input image, compressed output, and network parameters. We apply the lapped transform technique, an extended version of the discrete cosine transform, and run length encoding before Lempel-Ziv-Welch coding to the proposed algorithms to improve both quality and compression rate in image compression scheme. We extensively conduct computational experiments to verify the our methods and find that the proposed algorithms achieve not only balancing the total energy consumption among sensor nodes and, thus, increasing the overall network lifetime, but also reducing block noise in image compression.},
keywords={},
doi={10.1587/transcom.E93.B.3438},
ISSN={1745-1345},
month={December},}
Copy
TY - JOUR
TI - Low-Complexity and Energy-Efficient Algorithms on Image Compression for Wireless Sensor Networks
T2 - IEICE TRANSACTIONS on Communications
SP - 3438
EP - 3447
AU - Phat NGUYEN HUU
AU - Vinh TRAN-QUANG
AU - Takumi MIYOSHI
PY - 2010
DO - 10.1587/transcom.E93.B.3438
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E93-B
IS - 12
JA - IEICE TRANSACTIONS on Communications
Y1 - December 2010
AB - This paper proposes two algorithms to balance energy consumption among sensor nodes by distributing the workload of image compression tasks within a cluster on wireless sensor networks. The main point of the proposed algorithms is to adopt the energy threshold, which is used when we implement the exchange and/or assignment of tasks among sensor nodes. The threshold is well adaptive to the residual energy of sensor nodes, input image, compressed output, and network parameters. We apply the lapped transform technique, an extended version of the discrete cosine transform, and run length encoding before Lempel-Ziv-Welch coding to the proposed algorithms to improve both quality and compression rate in image compression scheme. We extensively conduct computational experiments to verify the our methods and find that the proposed algorithms achieve not only balancing the total energy consumption among sensor nodes and, thus, increasing the overall network lifetime, but also reducing block noise in image compression.
ER -
English
