Stochastic systems: estimation, identification and adaptive control
Stochastic systems: estimation, identification and adaptive control
Multiclass queueing systems: polymatroidal structure and optimal scheduling control
Operations Research - Supplement to Operations Research: stochastic processes
The Complexity of Optimal Queuing Network Control
Mathematics of Operations Research
Power allocation and routing in multibeam satellites with time-varying channels
IEEE/ACM Transactions on Networking (TON)
Probability in the Engineering and Informational Sciences
Scheduling and performance limits of networks with constantly changing topology
IEEE Transactions on Information Theory
Optimal bandwidth allocation in a delay channel
IEEE Journal on Selected Areas in Communications
Optimality of myopic sensing in multichannel opportunistic access
IEEE Transactions on Information Theory
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In this paper we study an optimal server allocation problem, where a single server is shared among multiple queues based on the queue backlog information. Due to the physical nature of the system this information is delayed, in that when the allocation decision is made, the server only has the backlog information from an earlier time. Queues have different arrival processes as well as different buffering/holding costs. The objective is to minimize the expected total discounted holding cost over a finite or infinite horizon. We introduce an index policy where the index of a queue is a function of the state of the queue. Our primary interest is to characterize conditions under which this index policy is optimal. We present a fairly general method bounding the reward of serving one queue instead of another. Using this result, sufficient conditions on the optimality of the index policy can be derived for a variety of arrival processes and packet holding costs. These conditions are in general in the form of sufficient separation among indices, and they characterize the part of the state space where the index policy is optimal. We provide examples and derive the indices and illustrate the region where the index policy is optimal.