考慮適應界限值之有限誤差的無線感測網路資料壓縮與聚合

Bounded-Error Data Compression and Aggregation with Adaptive Bound Value in Wireless Sensor Network

陳禹豪(Yu-Hao Chen)

指導教授 ： 張瑞益

國立臺灣大學/工學院/工程科學及海洋工程學研究所/碩士(2013年)

https://doi.org/10.6342/NTU.2013.03069

摘要

無線感測裝置往往布置於無法持續供給電力的狀況下，且裝置體積微小，蓄電能力有限，因此如何減少耗電量以延長無線感測網路的使用壽命成為重要的研究議題。在部分實際應用中可容許資料誤差的情況下，有限誤差資料壓縮(Bounded Error Data Compression，簡稱BEC)是首度提出可控制誤差界限的失真壓縮演算法，以解決傳統失真壓縮可能導致資料嚴重失真的問題，以同時維持良好壓縮率並控制誤差程度。然而其時間相關性壓縮演算法使誤差界限無法發揮效益。因此本研究針對此缺失做改進，提出改進有限誤差的無線感測網路資料壓縮(Improved Bounded-Error Data Compression in Wireless Sensor Network，簡稱IBEC)。
IBEC將有限誤差的概念結合運行長度編碼(Run-Length Encoding)壓縮法，提出BERLE(Bounded-Error Run-Length Encoding)，以達到連續壓縮效果，提升壓縮率。
本研究以四種不同相關程度的實際感測資料驗證IBEC之效能，並與BEC做比較。結果顯示在誤差界限為1%，時間相關程度較高的資料在IBEC中可較BEC至少提升34.5%壓縮率，並節省35.1%耗電量。無論在任何類型資料，壓縮率及能源使用效率上IBEC表現皆明顯比BEC提升，因此IBEC更適合應用於無線感測網路。

關鍵字

無線感測網路 ； 有限誤差 ； 資料壓縮 ； 時間相關性 ； 適應性 ； 能源效率

並列摘要

Energy supply is the critical issue in wireless sensor networks (WSNs), as the transmission of the data is the largest energy consumption especially. In previous study, BEC shows that the power consumption and information loss could be balanced by bounded-error compression and aggregation. However, the temporal correlated compression method of BEC may make error bound work inefficiently.
In this paper, we propose Improved Bounded-Error Data Compression in Wireless Sensor Network (IBEC). IBEC uses Bounded-Error Run-Length Encoding (BERLE) to make sensed data compressed continuously to enhance compression ratio.
We use four real-world sensed datasets to evaluate the performance of IBEC, and make comparison with BEC. The simulation results reveal that, when the error bound is 1%, IBEC can at least enhance 34.5% compression ratio and save 35.1% energy than BEC in high temporal correlated cases. The experiment results show that IBEC is better than BEC in all types of cases. Therefore, IBEC can make WSNs work more efficiently in power consumption.

並列關鍵字

Wireless sensor networks ； bounded error ； data compression ； temporal correlation ； adaptive ； energy efficiency

參考文獻

[1] K. Dasgupta, K. Kalpakis, and P. Namjoshi, "An Efficient Clustering-based Heuristic for Data Gathering and Aggregation in Sensor Networks," in Proceedings of Wireless Communications and Networking Conference, 2003.

[5] I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “Wireless sensor networks: A survey,” Computer Networks, Vol. 38, pp. 393-422, May 2002.

[6] Y. Liang and W. Peng, “Minimizing energy consumptions in wireless sensor networks via two-modal transmission,” ACM SIGCOMM, Vol. 40, pp. 12-18, January 2010.

[8] Taguchi, G, “Introduction to quality engineering: designing quality into products and processes,” Tokyo : Asian Productivity Organization, 1986.

[9] P. Poli, P. Moll, D. Puech, F. Rabier, and S. B. Healy, "Quality Control, Error Analysis, and Impact Assessment of FORMOSAT-3/COS MIC in Numerical Weather Prediction," Terrestrial, Atmospheric and Oceanic Sciences, vol. 20, pp. 101-113, 2009.