Diagnostic powertracing for sensor node failure analysis

  • Authors:
  • Mohammad Maifi Hasan Khan;Hieu K. Le;Michael LeMay;Parya Moinzadeh;Lili Wang;Yong Yang;Dong K. Noh;Tarek Abdelzaher;Carl A. Gunter;Jiawei Han;Xin Jin

  • Affiliations:
  • University of Illinois, Urbana-Champaign, N. Goodwin Ave;University of Illinois, Urbana-Champaign, N. Goodwin Ave;University of Illinois, Urbana-Champaign, N. Goodwin Ave;University of Illinois, Urbana-Champaign, N. Goodwin Ave;University of Illinois, Urbana-Champaign, N. Goodwin Ave;University of Illinois, Urbana-Champaign, N. Goodwin Ave;University of Illinois, Urbana-Champaign, N. Goodwin Ave;University of Illinois, Urbana-Champaign, N. Goodwin Ave;University of Illinois, Urbana-Champaign, N. Goodwin Ave;University of Illinois, Urbana-Champaign, N. Goodwin Ave;University of Illinois, Urbana-Champaign, N. Goodwin Ave

  • Venue:
  • Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks
  • Year:
  • 2010

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Abstract

Troubleshooting unresponsive sensor nodes is a significant challenge in remote sensor network deployments. This paper introduces the tele-diagnostic powertracer, an in-situ troubleshooting tool that uses external power measurements to determine the internal health condition of an unresponsive host and the most likely cause of its failure. We developed our own low-cost power meter with low-bandwidth radio to report power measurements and findings, hence allowing remote (i.e., tele-) diagnosis. The tool was deployed and tested in a remote solar-powered sensing network for acoustic and visual environmental monitoring. It was shown to successfully distinguish between several categories of failures that cause unresponsive behavior including energy depletion, antenna damage, radio disconnection, system crashes, and anomalous reboots. It was also able to determine the internal health conditions of an unresponsive node, such as the presence or absence of sensing and data storage activities (for each of multiple sensors). The paper explores the feasibility of building such a remote diagnostic tool from the standpoint of economy, scale and diagnostic accuracy. To the authors' knowledge, this is the first paper that presents a remote diagnostic tool that uses power measurements to diagnose sensor system failures.