DustDoctor: A Self-Healing Sensor Data Collection System

This paper presents a tool, called DustDoctor, for troubleshooting sensor data fusion systems where data are 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).

Provided by: University of Illinois Topic: Data Management Date Added: Feb 2011 Format: PDF

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