TY - GEN
T1 - Diagnostic powertracing for sensor node failure analysis
AU - Khan, Mohammad Maifi Hasan
AU - Le, Hieu K.
AU - LeMay, Michael
AU - Moinzadeh, Parya
AU - Wang, Lili
AU - Yang, Yong
AU - Noh, Dong K.
AU - Abdelzaher, Tarek
AU - Gunter, Carl A.
AU - Han, Jiawei
AU - Jin, Xin
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
KW - energy
KW - sensor networks
KW - troubleshooting
UR - http://www.scopus.com/inward/record.url?scp=77954507274&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77954507274&partnerID=8YFLogxK
U2 - 10.1145/1791212.1791227
DO - 10.1145/1791212.1791227
M3 - Conference contribution
AN - SCOPUS:77954507274
SN - 9781605589886
T3 - Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN '10
SP - 117
EP - 128
BT - Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN '10
T2 - 9th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2010
Y2 - 12 April 2010 through 16 April 2010
ER -