DustDoctor: A self-healing sensor data collection system

Mohammad Maifi Hasan Khan, Hossein Ahmadi, Gulustan Dogan, Kannan Govindan, Raghu Ganti, Theodore Brown, Jiawei Han, Prasant Mohapatra, Tarek Abdelzaher

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This demonstration presents a tool, called DustDoctor, for troubleshooting sensor data fusion systems in which data is combined from multiple heterogeneous sources to compute actionable information. Application examples include target detection, critical infrastructure monitoring, and participatory sensing. In such systems, the correctness of end results may become compromised for a variety of possible reasons, such as node malfunction, bugs, environmental conditions unfavorable to certain sensors, or assumption mismatches (such as use of incompatible units on different nodes of the same distributed computation). DustDoctor adapts algorithms borrowed from previous discriminative mining literature to analyze data fusion flow graphs, called provenance graphs, and isolate sources and conditions correlated with anomalous results. This information is subsequently used to isolate malfunctioning components or filter out erroneous reports. We demonstrate our approach on MicaZ motes, running a simple data collection application, where users are allowed to inject a variety of different emulated faults, leaving it to DustDoctor to find and isolate them to prevent contamination of fusion results.

Original languageEnglish (US)
Title of host publicationProceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN'11
Pages127-128
Number of pages2
StatePublished - Jun 23 2011
Event10th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN'11 - Chicago, IL, United States
Duration: Apr 12 2011Apr 14 2011

Publication series

NameProceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN'11

Other

Other10th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN'11
CountryUnited States
CityChicago, IL
Period4/12/114/14/11

Keywords

  • Data fusion
  • Multi-sensor fusion
  • Quality of information
  • Wireless sensor networks

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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  • Cite this

    Khan, M. M. H., Ahmadi, H., Dogan, G., Govindan, K., Ganti, R., Brown, T., Han, J., Mohapatra, P., & Abdelzaher, T. (2011). DustDoctor: A self-healing sensor data collection system. In Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN'11 (pp. 127-128). [5779078] (Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN'11).