CAREER: Design and Analysis of Performance-Critical Wireless Sensor Networks: A Fusion-Centric Approach

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Wireless Sensor Networks (WSNs) have the potential to monitor the physical world at an unprecedented spatio-temporal scale. Recently, WSNs have been deployed for many emerging performance-critical applications such as monitoring important infrastructures (power grid and bridges) and detecting natural hazards (volcanoes and earthquakes). However, deeply integrated with the physical world, WSNs often suffer from significant performance variations caused by uncertainties including environmental noise, dynamics of physical phenomena, and network deployment inaccuracy. This project develops a principled network design and analysis approach to performance assurance of WSNs. In contrast to existing heuristics-based solutions, this approach adopts data fusion, an advanced information processing scheme, to enable sensors to efficiently collaborate in delivering predictable network performance. This project has four aims: 1) A framework for analyzing spatio-temporal sensing performance based on established data fusion models. The analysis captures fundamental relationship between spatio-temporal coverage defined by event detection and false alarm probabilities, fusion models, network density, and physical uncertainties including noise and deployment inaccuracy. 2) Data fusion schemes that exploit mobile sensors to reconfigure the capability of a network in response to physical dynamics. 3) A unified fusion and communication architecture abstraction that allows developers to implement and optimize network protocols using group-level primitives. 4) A model-driven medium access control protocol that can achieve predictable throughput and delay in collaborative data processing.This project will have impact in numerous critical applications that require stringent sensing and communication performance. The results of this project will be integrated into outreach activities, curriculum development, and student mentoring.