Estimation Based Distributed QoS Pricing and Scheduling for Elastic Internet Services

We present a State Estimation based Internet traffic flow control system where the objective is to maximize the aggregate bandwidth utility of network sources over their transmission rates. The network links and sources are viewed as processors of distributed computation and the control mechanism is based on estimation and optimization framework to solve the dual problem. The novelty of our approach is that it allows network sources to estimate link bandwidth prices, based on the network state, rather than depending on the continuous price feedback from the network links. This is primarily to reduce the computational and communicational overhead of the routing process and to enable efficient resource allocation. The estimation framework also serves as network Management System to control hardware malfunctions, improves network monitoring and eliminates anomalies, such as measurement noise another discrepancies between network system models that typically leads to poor network performance. The approach is validated using two case studies in congestion and rate control which demonstrate favorable results in terms of enhanced data delivery with fewer packet losses and retransmissions. Moreover, our improved optimization framework in turn improves on network stability and responsiveness by allowing reduced buffer occupancy over congested links, which further enables low packet loss and low service delays.