Dynamic resource allocation of GPS queues with leaky buckets

We study the problem of dynamic resource allocation of a GPS server with two traffic classes when the leaky bucket scheme is employed as a traffic policing mechanism. Three popular input traffic models - independent Poisson arrival, autoregressive model, and partially observed traffic (hidden Markov model) - are investigated. Theoretically, optimal control can be obtained by a basic dynamic programming algorithm. However, such a solution is computationally prohibitive due to the curse of dimensionality. Instead, we propose several heuristic policies with improvements using rollout, parallel rollout, and hindsight optimization techniques under the aforementioned traffic models and show that these techniques can significantly reduce the penalty associated with delays and dropped packets.