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This paper appears in: Global Telecommunications Conference, 2007. GLOBECOM '07. IEEE
Publication Date: 26-30 Nov. 2007
On page(s): 2678-2683
ISBN: 978-1-4244-1043-9


The paper introduces a new algorithm for rate allocation in a multi-service Internet. The algorithm meets delay requirements of different services and provides fairness and congestion control. A performance comparison with other leading protocols is also carried out. 

This paper appears in: Quality of Service, 2008. IWQoS 2008. 16th International Workshop on
Publication Date: 2-4 June 2008
On page(s): 269-278
ISSN: 1548-615X
ISBN: 978-1-4244-2084-1


There is growing evidence that a new generation of potentially high-revenue applications requiring quality of service (QoS) guarantee are emerging. Current methods of QoS provisioning have scalability concerns and cannot guarantee end-to-end delay. For a theoretical fluid model, we derive four distributed rate and delay controls accounting for their bandwidth and end-to-end delay requirements while also allowing for multiple flow priorities. We show that two of them are globally stable in the presence of arbitrary information time lags and two are globally stable without time lags. The global stability in the presence of time lags of the later two is studied numerically. Under all controls, the stable flow rates attain the end-to-end delay requirements. We also show that by enhancing the network with bandwidth reservation and admission control, minimum rate is also guaranteed by our controls. By guaranteeing end- to-end delays, our controls facilitate router buffer sizing that prevent buffer overflow in the fluid model. The distributed rate- delay combined control algorithms provide a scalable theoretical foundation for a QoS-guarantee control plane in current and in "clean slate" IP networks. To translate the theory into practice, we describe a control plane protocol facilitating our controls in the edge routers. The stability and performance of discrete time versions of our controls are demonstrated numerically in a widely spanned real network topology.


To address end-to-end quality of service (QoS) requirements, we derive a novel distributed combined rate and end-to-end delay control in a network serving multi-class flows with priority packet scheduling. We show that the control is globally asymptotically stable without information time lags. The stable flows attain the end-to-end delay requirements and have no packet loss. We also show that by enhancing

the network with bandwidth reservation and admission control, minimum rate is also guaranteed. The stability with very long time lags of a discrete time version control with non-greedy flows and random packet arrivals is studied numerically by an NS2 packet-based simulation of the Australian Academic and Research Network.



Growing demand for streaming, voice and interactive gaming applications emphasize the importance of quality of service (QoS) provisioning in the Internet, particularly the need for maximum end-to-end delay guarantee. Current methods of QoS provisioning have either scalability concerns or cannot guarantee end-to-end delay with acceptable packet loss unless bandwidth is over-provisioned. While low jitter guarantee is required for streaming applications, maximum end-to-end delay is also required for VoIP and interactive games. We propose, analyze the stability and demonstrate the viability of three combined rate and end-to-end delay controls. The stability analysis is done on a fluid network model with greedy flows showing that all controls are globally asymptotically stable without information time lags and one of them is also globally asymptotically stable with arbitrary time lags. The viability of one of our controls and its advantage over Differentiated Services is demonstrated by implementing it in edge and core routers and monitoring the rate, end-to-end delay and packet loss of all flows in a six-node core network with long delay links. The viability of the two other controls is shown by detailed NS2 packet-based simulations of an eight-node real core network.






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