A Flow Aggregation Method for the Scalable and Efficient Quality of Service Support in Next Generation Networks

Date

2013-12-13

Author

Sanli, Mustafa
Schmidt, Şenan Ece
Guran, Hasan Cengiz

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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The services in the Next Generation Network (NGN) will be created on demand by the customers and will require end-to-end Quality of Service (QoS) for each flow. A very significant component for the end-to-end QoS support in the Internet is the packet schedulers in the routers. The complexity of the packet scheduling algorithms increases with the number of flows. As a solution, flow aggregation decreases the number of flows processed by the scheduler. The previous work in the literature proves that if the flow aggregator is fair, the end-to-end delay bounds of the aggregated flows are preserved and suggests limiting the service rate for the aggregate flow to achieve fairness in the expense of a lower utilization of the network resources. In this paper, we present a new method for flow aggregation, which relaxes this limit on the aggregate service rate, to increase the link utilization. We analytically show that our aggregation method is fair. Consequently, the end-to-end delay bounds in the network are preserved. In addition, we provide simulation results to demonstrate the decreased average delay of the aggregated flow.

Subject Keywords

Fair queuing algorithms, Performance, Management

URI

https://hdl.handle.net/11511/55877

Conference Name

IEEE Global Communications Conference (GLOBECOM)

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

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Citation Formats

M. Sanli, Ş. E. Schmidt, and H. C. Guran, “A Flow Aggregation Method for the Scalable and Efficient Quality of Service Support in Next Generation Networks,” presented at the IEEE Global Communications Conference (GLOBECOM), Atlanta, GA, 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55877.