IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 13, NO. 1, FEBRUARY
2005.
This paper is considered a network with both controllable and uncontrollable flows. Uncontrollable flows are typically generated from applications with stringent QoS requirements and are given high priority. On the other hand, controllable flows are typically generated by elastic applications and can adapt to the available link capacities in the network. We provide a general model of such a system and analyze its queueing behavior. Specially, we obtain a lower bound and an asymptotic upper bound for the tail of the workload distribution at each link in the network. These queueing results provide us with guidelines on how to design a feedback flow control system. Simulation results showthat the lower bound and asymptotic upper bound are quite accurate and that our feedback control method can effectively control the queue length in the presence of both controllable and uncontrollable traffic. Finally, we describe a distributed strategy that uses the notion of Active Queue Management (AQM) for implementing our flow control solution.
This paper is considered a network with both controllable and uncontrollable flows. Uncontrollable flows are typically generated from applications with stringent QoS requirements and are given high priority. On the other hand, controllable flows are typically generated by elastic applications and can adapt to the available link capacities in the network. We provide a general model of such a system and analyze its queueing behavior. Specially, we obtain a lower bound and an asymptotic upper bound for the tail of the workload distribution at each link in the network. These queueing results provide us with guidelines on how to design a feedback flow control system. Simulation results showthat the lower bound and asymptotic upper bound are quite accurate and that our feedback control method can effectively control the queue length in the presence of both controllable and uncontrollable traffic. Finally, we describe a distributed strategy that uses the notion of Active Queue Management (AQM) for implementing our flow control solution.