Optimal Bandwidth Allocation for Dynamically Priced Network Services

Abstract

We have proposed the use of dynamically priced network services to provide QoS guarantees within a network. End-to-end QoS can be achieved by using several of these services, perhaps from different ISPs. In this paper we consider the problem of determining the bandwidth to allocate each service in order to maximize revenue, assuming that a single ISP can estimate the demand curves for each of its services. We develop and analyze two heuristics which provide time versus revenue tradeoffs. To determine the optimality of our solutions, we map the optimal allocation problem into a multiple choice multidimensional knapsack problem that approaches optimality as we increase the number of bandwidth allocation choices for each service. Our first heuristic, IterLP, achieves revenue close to 99% of the optimal solution, achieving this result in a very short time. The second heuristic, IterGreedy, achieves approximately 93% optimality, but executes more quickly than IterLP.