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Mobile Information Systems Volume 2017 ,2017-02-22
A Novel Low-Cost Real-Time Power Measurement Platform for LoWPAN IoT Devices
Research Article
Yang Liu 1 , 2 Yubing Wang 2 Weiwei Gao 2 Wuxiong Zhang 1 , 2 Hua Qian 3 Yang Yang 1 , 2
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DOI:10.1155/2017/8713873
Received 2016-11-25, accepted for publication 2017-01-29, Published 2017-01-29
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摘要

With the rapid development of technology and application for Internet of Things (IoT), Low-Power Wireless Personal Area Network (LoWPAN) devices are more popularly applied. Evaluation of power efficiency is important to LoWPAN applications. Conventional method to evaluate the power efficiency of different LoWPAN devices is as follows: first measure the current of the devices under working/idle/sleep state and then make an average and estimation of the lifetime of batteries, which deeply relied on the accuracy of testing equipment and is not that accurate and with high cost. In this work, a low-cost, real-time power measurement platform called PTone is proposed, which can be used to detect the real-time power of LoWPAN devices (above 99.63%) and be able to determine the state of each module of DUT system. Based on the PTone, a novel abnormal status diagnosis mechanism is proposed. The mechanism can not only judge abnormal status but also find accurate abnormal status locating and classify abnormal status accurately. According to the method, each state of Device Under Test (DUT) during wireless transmission is estimated, different abnormal status can be classified, and thus specific location of abnormal module can be found, which will significantly shorten the development process for LoWPAN devices and thus reduce costs.

授权许可

Copyright © 2017 Yang Liu et al. 2017
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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通讯作者

Wuxiong Zhang.Shanghai Institute of Microsystem and Information Technology, Key Laboratory of Wireless Sensor Network and Communication, Chinese Academy of Sciences (CAS), Shanghai, China, cas.cn;Shanghai Research Center for Wireless Communications (WiCO), Shanghai, China, wico.sh.wuxiong.zhang@wico.sh

推荐引用方式

Yang Liu,Yubing Wang,Weiwei Gao,Wuxiong Zhang,Hua Qian,Yang Yang. A Novel Low-Cost Real-Time Power Measurement Platform for LoWPAN IoT Devices. Mobile Information Systems ,Vol.2017(2017)

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参考文献
[1] H. Hosni, F. Mhamdi. A filter correlation method for feature selection. :59-63. DOI: 10.1109/JPROC.2013.2244053.
[2] R. Perdisci, D. Ariu, P. Fogla, G. Giacinto. et al.(2009). McPAD: a multiple classifier system for accurate payload-based anomaly detection. Computer Networks.53(6):864-881. DOI: 10.1109/JPROC.2013.2244053.
[3] D. Ariu, R. Tronci, G. Giacinto. (2011). HMMPayl: an intrusion detection system based on Hidden Markov Models. Computers and Security.30(4):221-241. DOI: 10.1109/JPROC.2013.2244053.
[4] C. Villani, D. Balsamo, D. Brunelli, L. Benini. et al.Ultra-low power sensor for autonomous non-invasive voltage measurement in IoT solutions for energy efficiency. .9517:93-95. DOI: 10.1109/JPROC.2013.2244053.
[5] H. Chen, Y. Chen, D. H. Summerville. (2011). A survey on the application of FPGAs for network infrastructure security. IEEE Communications Surveys and Tutorials.13(4):541-561. DOI: 10.1109/JPROC.2013.2244053.
[6] C. P. Ravikumar, M. Hirech, X. Wen. Test strategies for low power devices. :728-733. DOI: 10.1109/JPROC.2013.2244053.
[7] A. B. Dolgov, R. Zane. Low-power wireless medical sensor platform. :2067-2070. DOI: 10.1109/JPROC.2013.2244053.
[8] C. P. Shapiro. (1977). Classification by maximum posterior probability. The Annals of Statistics.5(1):185-190. DOI: 10.1109/JPROC.2013.2244053.
[9] C. Kim, S.-M. S. Kang. A low-power reduced swing single clock flip-flop. :806-809. DOI: 10.1109/JPROC.2013.2244053.
[10] J.-X. Zhang, Q.-H. Zhong, Y.-P. Dai, Z. Liu. et al.A new de-noising method based on wavelet transform and transforming Hampel filter. .2:2147-2151. DOI: 10.1109/JPROC.2013.2244053.
[11] J. Wang, J. Li, S. L. Ho, W. Y. Chau. et al.(2012). Study and experimental verification of a rectangular printed-circuit-board wireless transfer system for low power devices. IEEE Transactions on Magnetics.48(11):3013-3016. DOI: 10.1109/JPROC.2013.2244053.
[12] R. Odai, Y. Taniguchi, M. Kumoi. (2010). Multivalued document classification by Relevance Vector Machine in terms of maximum posterior probability. Abstracts of Annual Conference of Japan Society for Management Information:37. DOI: 10.1109/JPROC.2013.2244053.
[13] J. Li, X. Li, W. Zhang. A filter feature selection method based LLRFC and redundancy analysis for tumor classification using gene expression data. :2861-2867. DOI: 10.1109/JPROC.2013.2244053.
[14] N. Dharmaweera, R. Parthiban. Reducing power consumption in an optical circuit-switched core network by switching off amplifiers. :532-537. DOI: 10.1109/JPROC.2013.2244053.
[15] R. K. Pearson, Y. Neuvo, J. Astola, M. Gabbouj. et al.The class of generalized hampel filters. :2501-2505. DOI: 10.1109/JPROC.2013.2244053.
[16] X. Wen. Low-power testing for low-power devices. . DOI: 10.1109/JPROC.2013.2244053.
[17] D. Wang, Y. Zhou. Sparse posterior probability support vector machines. :396-399. DOI: 10.1109/JPROC.2013.2244053.
[18] F. Knutti, N. Tobler, H. Mathis. Low-power voting device for use in education and polls employing TI's CC2530 RF CHIP. :221-224. DOI: 10.1109/JPROC.2013.2244053.
[19] K. Wang, J. J. Parekh, S. J. Stolfo. (2006). Anagram: a content anomaly detector resistant to mimicry attack. Recent Advances in Intrusion Detection.4219:226-248. DOI: 10.1109/JPROC.2013.2244053.
[20] S. Davidson. (2010). About the power problem [review of ‘power-aware testing and test strategies for low power devices’ (Girard, P., Eds., et.; 2010)]. IEEE Design & Test of Computers.27(6):72-73. DOI: 10.1109/JPROC.2013.2244053.
[21] Y. Higami, S. Y. Kobayashi, Y. Takamatsu. A method to reduce power dissipation during test for sequential circuits. :326-331. DOI: 10.1109/JPROC.2013.2244053.
[22] Md. Sakhawat Hossen, A. F. M. Sultanul Kabir, R. H. Khan, A. Azfar. et al.(2010). Interconnection between 802.15.4 devices and IPv6: implications and existing approaches. IJCSI International Journal of Computer Science Issues.7(1):19-31. DOI: 10.1109/JPROC.2013.2244053.
[23] N. El Aboudi, L. Benhlima. Review on wrapper feature selection approaches. . DOI: 10.1109/JPROC.2013.2244053.
[24] Z. Popovic, E. A. Falkenstein, D. Costinett, R. Zane. et al.(2013). Low-power far-field wireless powering for wireless sensors. Proceedings of the IEEE.101(6):1397-1409. DOI: 10.1109/JPROC.2013.2244053.
[25] X. Xie, Q. Zhou, K. Li, A. Beling. et al.1.8 watt RF power and 60
[26] power conversion efficiency based on photodiode flip-chip-bonded on diamond. . DOI: 10.1109/JPROC.2013.2244053.
[27] P. Girard, N. Nicolici, X. Wen. (2010). Power-Aware Testing and Test Strategies for Low Power Devices. DOI: 10.1109/JPROC.2013.2244053.
[28] C. Krügel, T. Toth, E. Kirda. Service specific anomaly detection for network intrusion detection. :201-208. DOI: 10.1109/JPROC.2013.2244053.
[29] G. Ortiz, M. Leibl, J. Huber, J. W. Kolar. et al.(2016). Design and experimental testing of a resonant DC-DC converter for solid-state transformers. IEEE Transactions on Power Electronics.PP(99):1. DOI: 10.1109/JPROC.2013.2244053.
[30] K. Keikhosravy, P. Kamalinejad, S. Mirabbasi, K. Takahata. et al.An ultra-low-power monitoring system for inductively coupled biomedical implants. :2283-2286. DOI: 10.1109/JPROC.2013.2244053.
[31] D. H. Summerville, K. M. Zach, Y. Chen. Ultra-lightweight deep packet anomaly detection for Internet of Things devices. . DOI: 10.1109/JPROC.2013.2244053.
[32] A. Bendale, T. Boult. Reliable posterior probability estimation for streaming face recognition. :56-63. DOI: 10.1109/JPROC.2013.2244053.
[33] K. Wang, S. J. Stolfo. (2004). Anomalous payload-based network intrusion detection. Lecture Notes in Computer Science.3224:203-222. DOI: 10.1109/JPROC.2013.2244053.
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