CSR: Small: Collaborative Research: Autonomous Failure Detection and Recovery in Networked Embedded Systems

Developers of networked embedded systems often find it difficult to diagnose bugs. A key observation is that in such systems, it can be beneficial to exploit domain knowledge about events in the physical world to detect failures. For example, in a sensor network deployment, knowing that the received signal strength of a radio transmission will normally decrease over distance, the application developer can enforce runtime checks to detect faulty nodes based on their relative distances to the source and the orderings of their received signal strength.

Based on this intuition, this project addresses the challenge of developing correct, resilient, and reliable networked embedded systems by (i) proposing, developing, and evaluating a methodology of using physical events to detect software bugs, (ii) developing software libraries and APIs to facilitate easy access to physical event constraints by application developers, and (iii) evaluating the effectiveness of the software libraries using real-world applications.

The completed framework could significantly reduce the debugging and maintenance costs for complicated networked embedded systems, and improve their reliability. Beyond such direct social and economic benefits, the broader impacts of this work include: (i) improving curriculum with hands-on debugging sessions; (ii) raising interest in technology among high school seniors through a Pre-Collegiate Research Scholars Program; (iii) supporting talented female and under-represented minority PhD students to successfully accomplish their doctoral studies; (iv) disseminating research results through high-quality publications, high-profile tutorials, and open-source sites.