TY - GEN
T1 - Adaptive control of sensor networks for detection of percolating faults
AU - Srivastav, Abhishek
AU - Ray, Asok
AU - Phoha, Shashi
PY - 2009
Y1 - 2009
N2 - A complex network of interdependent components is susceptible to percolating faults. Sensor networks deployed for real-time detection and monitoring of such systems require adaptive re-distribution of resources for an energy-aware operation. This paper presents a statistical mechanical approach to adaptive self-organization of a sensor network for detection and monitoring of percolating faults. A complex dynamical system of interdependent components (e.g. computer and social network) is represented as an Ising-like model where component states are modeled as spins, and interactions as ferromagnetic couplings. Using a recursive prediction and correction methodology the sensor network is shown to adaptively selforganize to the dynamic environment and real-time detection and monitoring is enabled. The algorithm is validated on a test-bed simulating the operation 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.
AB - A complex network of interdependent components is susceptible to percolating faults. Sensor networks deployed for real-time detection and monitoring of such systems require adaptive re-distribution of resources for an energy-aware operation. This paper presents a statistical mechanical approach to adaptive self-organization of a sensor network for detection and monitoring of percolating faults. A complex dynamical system of interdependent components (e.g. computer and social network) is represented as an Ising-like model where component states are modeled as spins, and interactions as ferromagnetic couplings. Using a recursive prediction and correction methodology the sensor network is shown to adaptively selforganize to the dynamic environment and real-time detection and monitoring is enabled. The algorithm is validated on a test-bed simulating the operation 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.
UR - http://www.scopus.com/inward/record.url?scp=70449657552&partnerID=8YFLogxK
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U2 - 10.1109/ACC.2009.5160017
DO - 10.1109/ACC.2009.5160017
M3 - Conference contribution
AN - SCOPUS:70449657552
SN - 9781424445240
T3 - Proceedings of the American Control Conference
SP - 5797
EP - 5802
BT - 2009 American Control Conference, ACC 2009
T2 - 2009 American Control Conference, ACC 2009
Y2 - 10 June 2009 through 12 June 2009
ER -