ViRe: Virtual Reconfiguration Framework for Embedded Processing in Distributed Image Sensors

Image processing applications introduce new challenges to the design of sensor network systems via non-trivial in-network computation. As embedded processing becomes more complex, in-situ reconfiguration is seen as the key enabling technology to maintain and manage such systems. In dynamic event-driven heterogeneous sensor networks, reconfiguration also encompasses autonomous re-partitioning of applications across multiple tiers to provide a low-power responsive system by efficiently coping with variations in run-time resource usage and availability. Hence, we aim to provide an efficient lowpower macro-programming environment that supports multidimensional software reconfiguration of heterogeneous imaging networks. Working towards this initiative, we present the ViRe framework for mote-class devices based on data-centric application composition and execution. Applications, modeled as dataflow graphs, are composed from a library of pre-defined and reusable image processing elements. Concise scripts capture the wiring information and are used to install applications in the network, while execution on the nodes is performed via processor native code to minimize overhead. A lean run-time engine tightly monitors application execution to provide an efficient, robust and scalable support for complex reconfigurable embedded image processing. Thus, the system is able to lower application repartitioning overhead and minimize loss of work during software reconfiguration. Index Terms — Sensor Networks, Differential partitioning, Reconfiguration, Dataflow