Optimal control theory with economic applications
Optimal control theory with economic applications
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Heavy traffic resource pooling in parallel-server systems
Queueing Systems: Theory and Applications
Fluid approximation of a controlled multiclass tandem network
Queueing Systems: Theory and Applications
A framework for opportunistic scheduling in wireless networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Analysis of cycle stealing with switching times and thresholds
Performance Evaluation
Optimal scheduling in a multiserver stochastic network
ACM SIGMETRICS Performance Evaluation Review
Flow-level stability of data networks with non-convex and time-varying rate regions
Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Stability of Parallel Queueing Systems with Coupled Service Rates
Discrete Event Dynamic Systems
Assessing the efficiency of resource allocations in bandwidth-sharing networks
Performance Evaluation
Control Techniques for Complex Networks
Control Techniques for Complex Networks
On the Performance of a Two-User MIMO Downlink System in Heavy Traffic
IEEE Transactions on Information Theory
Delay-optimal opportunistic scheduling and approximations: the log rule
IEEE/ACM Transactions on Networking (TON)
Dynamic fluid-based scheduling in a multi-class abandonment queue
Performance Evaluation
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Motivated by scheduling in cellular wireless networks and resource allocation in computer systems, we study a service facility with two classes of users having heterogeneous service requirement distributions. The aggregate service capacity is assumed to be largest when both classes are served in parallel, but giving preferential treatment to one of the classes may be advantageous when aiming at minimization of the number of users, or when classes have different economic values, for example.We set out to determine the allocation policies that minimize the total number of users in the system. For some particular cases we can determine the optimal policy exactly, but in general this is not analytically feasible. We then study the optimal policies in the fluid regime, which prove to be close to optimal in the original stochastic model. These policies can be characterized by either linear or exponential switching curves. We numerically compare our results with existing approximations based on optimization in the heavy-traffic regime. By simulations we show that, in general, our simple computable switching-curve strategies based on the fluid analysis perform well.