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Optimal State Surveillance under Budget Constraints

Authors:
Praveen Bommannavar
Nicholas Bambos

Keywords: monitoring; surveillance; budget; resource allocation; dynamic programming

Abstract:
In this paper we consider the problem of monitor- ing an intruder in a setting where the number of opportunities to conduct surveillance is budgeted. Specifically, we consider a problem in which we model the state of an intruder in our system with a Markov chain of finite state space. These problems are considered in a setting in which we have a hard limit on the number of times we may view the state. Such a constraint is natural when considering surveillance where mobile devices are involved and battery power is at a premium. We consider the Markov chain together with an associated metric that measures the distance between any two states. We develop a policy to optimally (with respect to the specified metric) keep track of the state of the chain at each time step over a finite horizon when we may only observe the chain a limited number of times. The tradeoff captured is the budget for surveillance versus having a more accurate estimate of the state; the decision at each time step is whether or not to use an opportunity to observe the process.

Pages: 68 to 73

Copyright: Copyright (c) IARIA, 2010

Publication date: October 25, 2010

Published in: conference

ISSN: 2326-9383

ISBN: 978-1-61208-103-8

Location: Florence, Italy

Dates: from October 25, 2010 to October 30, 2010