Abstract
Resource aware operation of sensor networks requires adaptive re-organization to dynamically adapt to the operational environment. A complex dynamical system of interacting components (e.g., computer network and social network) is represented as a graph, component states as spins, and interactions as ferromagnetic couplings. Using an Ising-like model, the sensor network is shown to adaptively self-organize based on partial observation, and real-time monitoring and detection is enabled by adaptive redistribution of limited resources. The algorithm is validated on a test-bed that simulates the operations of a sensor network for detection of percolating faults (e.g. computer viruses, infectious disease, chemical weapons, and pollution) in an interacting multi-component complex system.
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This work has been supported in part by the U.S. Army Research Laboratory and the U.S. Army Research Office (ARO) under Grant No. W911NF-07-1-0376, by NASA under Cooperative Agreement No. NNX07AK49A, and by the U.S. Office of Naval Research under Grant No. N00014-08-1-0380.
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Srivastav, A., Ray, A. Self-organization of sensor networks for detection of pervasive faults. SIViP 4, 99–104 (2010). https://doi.org/10.1007/s11760-008-0101-4
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DOI: https://doi.org/10.1007/s11760-008-0101-4