ITR: Computation and Communication in Sensor Webs

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Traditional design approaches that treat the processor node, network, andsensor/actuator subsystems as distinctly independent components do notapply well to the domain of sensor webs. This is a result of sensor websystems being comprised of hundreds of thousands of small, autonomousdevices that dynamically engage or disengage in the generation of data. Nodes within these systems are deployed in an ad-hoc fashion, with noa-priori knowledge of network and sensor/actuator connectivity. These new requirements call for a new machine model that more closelysupports the sensor webs unique operational and behavioral requirements. This research focuses on a holistic system-centric approach thatdefines such a new integrated communications/computation machine model forsensor web nodes. The new machine model is expressed in terms of a Metainstruction set architecture (ISA). This Meta ISA defines primitivesystem operations, such as domain selections, data reduction, andbroadcast across ad hoc networks of nodes, much like the ISA of a CPUdefining the CPU's primitive operations. The Meta ISA enables consistentand reliable system level operation for dynamically changing numbers andlocations of sensors, and supports multimode data fusion. The Meta ISAexplicitly supports attribute based naming, which enables the dynamiccreation of unique knowledge domains across unknown numbers ofheterogeneous sensor types. A new routing protocol has is studied as an integral part of the integrated computation/communication model. The protocol is active inissuing and decoding Meta instructions throughout the sensorweb and has been designed specifically to support attribute-based namingand formation of knowledge domains across large ad hoc webs. The broader impact of this project includes the development of an educational focus area in the engineering of computer-based systems. Courses include embedded and real-time systems, sensor webs, run time software for embedded systems, and distributed systems. The project is achieving impact for both graduate and undergraduate students by integrating the research agenda and results into the classroom, and focusing collaborative activities. Software tools and hardware platforms developed in this project will enhance student laboratories for experimentation and projects.