Probabilistic-bandwidth guarantees with pricing in data-center networks

Abstract

Bandwidth-sharing in data-center networks is an important problem that affects the growth of multi-tenant datacenters. A promising solution approach is the use of advance reservations. Such systems are usually based on deterministic models, assuming users to have precise knowledge of bandwidth they require, which is unlikely. This work takes a deviation and proposes a probabilistic model, where bandwidth requirements are specified along with some probabilities. As user-estimate of bandwidth depends on the cost they incur, we tie up the model with differential pricing; and formulate bandwidth allocation as a two-phase - static and dynamic - optimization problem. We show that the problem in each phase is NP-hard. We develop a bandwidth-allocator that processes requests and defines bandwidth profiles for accepted requests by solving the optimization problems. Numerical studies show that, in comparison to the deterministic model, our model brings down the number of rejected requests significantly, while allocating more bandwidth and thereby increasing revenue for providers.