The complexity of Markov decision processes
Mathematics of Operations Research
Detection of abrupt changes: theory and application
Detection of abrupt changes: theory and application
On the self-similar nature of Ethernet traffic
SIGCOMM '93 Conference proceedings on Communications architectures, protocols and applications
Probabilistic modelling
Self-Similar Network Traffic and Performance Evaluation
Self-Similar Network Traffic and Performance Evaluation
Piecewise linear dynamic programming for constrained POMDPs
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
IEEE Transactions on Information Theory
Quickest Detection and Tracking of Spawning Targets Using Monopulse Radar Channel Signals
IEEE Transactions on Signal Processing
Nonparametric change detection and estimation in large-scale sensor networks
IEEE Transactions on Signal Processing
Decentralized quickest change detection
IEEE Transactions on Information Theory
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We consider the quickest detection of idle periods in multiple ON-OFF processes. At each time, only one process can be observed, and the observations are random realizations drawn from two different distributions depending on the current state (ON or OFF) of the chosen process. The objective is to catch an idle period in any of the ON-OFF processes as quickly as possible subject to a reliability constraint. We show that this problem presents a fresh twist to the classic problem of quickest change detection that considers only one stochastic process. A Bayesian formulation of the problem is developed for both infinite and finite number of processes based on the theory of partially observable Markov decision process (POMDP). While a general POMDP is PSPACE-hard, we show that the optimal decision rule has a simple threshold structure for the infinite case. For the finite case, basic properties of the optimal decision rule are established, and a low-complexity threshold policy is proposed which converges to the optimal decision rule for the infinite case as the number of processes increases. This problem finds applications in spectrum sensing in cognitive radio networks where a secondary user searches for idle channels in the spectrum.