Size-based Adaptive Bandwidth Allocation: Optimizing the Average QoS for Elastic Flows

Shan-Chieh Yang, Gustavo de Veciana

Abstract: With a view on improving user perceived performance on networks supporting elastic flows, e.g., multimedia/data file transfers, we identify the key properties that an online dynamic bandwidth allocation policy should have. We then propose a family of bandwidth allocation criteria which depends on the residual work of on-going transfers. Analysis and simulations show that allocating bandwidth in this fashion can improve the user perceived average bit transmission delay (BTD), i.e., delay/flow size, by up to 70% at 80% traffic load over traditional approaches. A simple implementation based upon TCP Reno, exemplifies how one might approach practically realizing such gains. Further studies on simple network topologies show that as the penetration of the proposed transport mechanism increases, users will have the proper incentives to upgrade from TCP Reno, and that the overall performance is better for all users once the penetration exceeds 20%.