Revenue Management in the Presence of Self-Similar Alpha-Stable Distributions

We consider the problem of maximizing network revenue from the perspective of bandwidth allocation and route selection. The objective is to perform offline maximization of revenue from served demands in the context of self-similar (long range dependent) traffic. We use an alpha-stable distribution for the aggregate demand volume to capture the appropriate level of traffic burstiness. We take a centralized view of the network topology, link capacity and demand. We use a new mean-risk modeling approach to that considers both the mean and the risk of bandwidth allocation. We also propose a risk measure appropriate for infinite variance alpha-stable distribution.