CAREER: PROSE: Providing Robustness in Systems of Embedded Sensors

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While sensor applications promise profound scientific and economic impacts on our society, their success is nonetheless determined by whether the sensor networks can provide a steady stream of correct data. This need for continuous data provisioning over a significant time period, however, imposes great challenges to the underlying system. Specifically, wireless sensor networks are prone to a large array of hazards, such as frequent node failures, congestion, and sensing errors. These challenges are further complicated by the fact that sensor systems are usually seriously energy constrained.This project has three main components: DADA, TARA, and MARA. DADA, a 2-Dimensional Adaptive Scheduling Framework, rapidly repairs network coverage and connectivity by cleverly waking up the redundant nodes that are needed for repairing holes created by the node failure. TARA, a Topology-Aware Resource Adaptation Framework, strives to increase the resource provisioning by bringing more sensor nodes online to accommodate those packets that contain valuable data, potentially regarding the source of the congestion. MARA, a Measurement Assurance and Robust Aggregation Framework, provides a set of data classification and cleansing tools that validate the data before they flow into the network. This project attempts to deliver the guarantee that sensor systems must gracefully recover themselves in the presence of network exceptions, in order to satisfy the application needs as well as lower the network management costs. In addition to technical papers that report the research results, this project will also produce a suite of software tools that will be made available to the community.