Optimal and Structured Call Admission Control Policies for Resource-Sharing Systems

Many communication and networking systems can be modeled as resource-sharing systems with multiple classes of calls. Call admission control (CAC) is an essential component of such systems. Markov decision process (MDP) tools can be applied to analyze and compute the optimal CAC policy that optimizes certain performance metrics of the system. But for most practical systems, it is prohibitively difficult to compute the optimal CAC policy using any MDP algorithm because of the "curse of dimensionality". We are, therefore, motivated to consider two families of structured CAC policies: reservation and threshold policies. These policies are easy to implement and have good performance in practice. However, since the number of structured policies grows exponentially with the number of call classes and the capacity of the system, finding the optimal structured policy is a complex unsolved problem. In this paper, we develop fast and efficient search algorithms to determine the parameters of the structured policies. We prove the convergence of the algorithms. Through extensive numerical experiments, we show that the search algorithms converge quickly and work for systems with large capacity and many call classes. In addition, the returned structured policies have optimal or near-optimal performance, and outperform those structured policies with parameters chosen based on simple heuristics