NeTS-NOSS: Algorithms and System Support for Data Integrity in Wireless Sensor Networks

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Wireless sensor networks with their ability of in situ and dense spatiotemporal sampling of physical phenomena have rapidly emerged as a valuable new class of instrument for the basic sciences. Like any instrument, however, sensor networks suffer from impairments that adversely impact the integrity of the sensed information about the physical phenomena. The causes of reduced integrity in sensor networks are many, and include various internal and external uncertainties in the sensing, processing, and communication elements of the system. Examples include calibration errors, faults, sensing channel degradation and obstructions, bio-fouling etc. This project is comprehensively addressing the integrity problem by studying its causes, understanding fundamental limits, developing algorithms and system support, and validating the approach in real-life. The two key elements of the overall approach are autonomous detection of integrity compromise, and resilient estimation and aggregation. Underlying these two are novel statistical and signal-processing techniques that exploit learned models of the physical phenomenon, the measurement process, and the faults which result in corrupted or missed data. In addition, the project is investigating approaches for guiding remediation of the causes of integrity problems, and for integrity-driven deployment of sensor network to achieve desired resilience. The research would result in a thorough understanding of integrity failure in sensor networks, and result in a toolkit of design tools and run-time software for ensuring high-integrity operation. These would be validated via terrestrial, under-soil, and aquatic ecological observation application, and also disseminated for broader use via the project web site at http://nesl.ee.ucla.edu/projects/integrity.