A game-theoretic model for capacity-constrained fair bandwidth allocation

Data stream providers face a hard decision to satisfy the requirements of their subscribers. Each user has a minimum and a maximum required bandwidth. The server should be able to decide which requests can be satisfied and how much bandwidth will be allocated to each. We present a theoretical framework in a distributed mechanism for fair bandwidth allocation on a network with various bottleneck links. In our model, a user is guaranteed a minimum bandwidth and charged a price for the bandwidth allocated. A utility function is defined over the allocated bandwidth for a specific maximum requested bandwidth. We then present a non-cooperative game with social welfare function to resolve users' conflicting bandwidth capacity requests at bottleneck links. We also show that our proposed game-theoretic solution guarantees fair bandwidth allocation as defined in our residual capacity fairness. In order to guarantee the minimum bandwidth requirement, we integrate an admission control mechanism in our solution. However, global optimal admission conditions are not easy to implement for large networks. Therefore, we propose a distributed admission scheme. As a result, the paper presents fair and practical distributed algorithms for bandwidth allocation and admission control in enterprise networks. Our simulation and evaluation study shows that the distributed approach is sufficiently close to the global optimal solution.