Optimization of Cybercafe Internet Service and Costs under Stochastic Demand

Abstract

We consider a set of cybercafes faced with an optimal choice of bandwidth for internet service under stochastic stationary demand. The choice is made over uniformly time horizons with a goal of optimizing costs. Considering customer demand and operating costs of internet service at cybercafes, we formulate a finite state markov decision process model where states of a markov chain represent possible states of demand for internet service. An operational cost matrix is generated; representing the long run measure of performance for the markov decision process problem. The problem is to determine an optimal bandwidth adjustment policy at cybercafes so that the long run operational costs are minimized for the given state of demand. Using dynamic programming, the optimal bandwidth adjustment policies are determined at least cost over a finite period planning horizon. Results from the case study demonstrate the existence of an optimal state-dependent option for bandwidth adjustment policy and costs of internet service at cybercafes.