Fair scheduling in wireless packet networks
IEEE/ACM Transactions on Networking (TON)
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Introduction to Stochastic Dynamic Programming: Probability and Mathematical
Introduction to Stochastic Dynamic Programming: Probability and Mathematical
Optimal Transmission Policies for Noisy Channels
Operations Research
A framework for opportunistic scheduling in wireless networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
ON PARALLEL QUEUING WITH RANDOM SERVER CONNECTIVITY AND ROUTING CONSTRAINTS
Probability in the Engineering and Informational Sciences
Probability in the Engineering and Informational Sciences
Scheduling over a time-varying user-dependent channel with applications to high-speed wireless data
Journal of the ACM (JACM)
Optimal resource scheduling in wireless multiservice systems with random channel connectivity
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Instability of the proportional fair scheduling algorithm for HDR
IEEE Transactions on Wireless Communications
Optimal Transmission Scheduling in Symmetric Communication Models With Intermittent Connectivity
IEEE Transactions on Information Theory
Dynamic server allocation to parallel queues with randomly varying connectivity
IEEE Transactions on Information Theory
QoE-aware optimization of multimedia flow scheduling
Computer Communications
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We investigate an optimal scheduling problem in a discrete-time, multiserver system of parallel queues. The servers are connected to the queues in a random fashion and scheduled packets complete service successfully with a given probability. This model is suitable for the study of dynamic packet scheduling problems in wireless systems. We study first a two-server system of two infinite-capacity queues with homogeneous arrival, service and connectivity assumptions. We use coupling arguments to prove that a ''Most Balancing'' scheduling policy is optimal, in a stochastic ordering sense, for this system. We then consider a finite-capacity, non-homogeneous, multi-server and multi-queue system. We develop a dynamic programming model to determine numerically the scheduling policy that optimizes a range of cost functions, including average total queue sizes. We also compare the performance of the optimal policy to that of a few other policies via simulations.