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- W2129623290 abstract "We describe a decentralized learning-based activation algorithm for a ZigBee-enabled unattended ground sensor network. Sensor nodes learn to monitor their environment in a low-power sleep mode, until an intruder is detected, then enter a full-power mode only if the benefit for doing so outweighs an energy cost. Our formulation accounts for the energy required to transmit and the probability of successful transmission in a crowded ZigBee network. Since these depend on the activity of other nodes, we propose a decentralized adaptive algorithm for sensor activation based on game theoretic principles. We show that the algorithm tracks the time-varying set of correlated equilibria of the problem, and illustrate performance through simulation. The algorithm is described as a stochastic approximation, with attendant differential inclusion analysis." @default.
- W2129623290 created "2016-06-24" @default.
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- W2129623290 date "2007-06-01" @default.
- W2129623290 modified "2023-10-16" @default.
- W2129623290 title "Decentralized Activation in a ZigBee-enabled Unattended Ground Sensor Network: A Correlated Equilibrium Game Theoretic Analysis" @default.
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- W2129623290 doi "https://doi.org/10.1109/icc.2007.645" @default.
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