Abstract
Our previous work [19–21] investigated optimal support of rate adaptive multimedia streams. In particular, we identified the optimal distribution of network bandwidth among competing streams, i.e., the optimal adaptation policy, which maximized our Quality of Service (QoS) metric, defined as the client average normalized time-average subscription level. The optimal adaptation policy (for a single link) was identified as granting the maximum subscription level to as many small volume streams as possible and granting the minimum subscription level to the remaining large volume streams, where stream volume is the product of the stream duration and the maximum subscription level, i.e., the number of bits associated with the stream at its finest resolution encoding. This type of volume discrimination may prove unsatisfactory to clients of large volume streams with heterogeneous QoS requirements.
In this work we introduce a link architecture supporting multiple service classes, where each service class is characterized by a distinct QoS guarantee. Intuitively, large volume streams, which would suffer under the volume discriminatory nature of the optimal adaptation policy for a single service class, might be willing to pay a price to obtain a higher degree of QoS protection offered by a “premium” service class. We introduce a capacity scaling appropriate for studying large numbers of clients sharing large capacity links. We identify the optimal adaptation policy for a link supporting multiple service classes, and obtain closed form expressions for the asymptotic QoS within each class under the optimal adaptation policy. We demonstrate that the same asymptotic QoS can be obtained under an appropriately designed admission control policy which eliminates the need for dynamic adaptation. Finally, we compare the benefits of offering multiple service classes over a single service class architecture in a case study which investigates how to multiplex small volume audio streams and large volume video streams on a congested link.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
N. Argiriou and L. Georgiadis. Channel sharing by rate adaptive streaming applications. In Proceedings of IEEE Infocom, 2002.
Alan Bain and Peter Key. Modelling the performance of in-call probing for multi-level adaptive applications. Technical Report MSR-TR-2002-06, Microsoft Research, October 2001.
B. Vickers, C. Alburquerque, and T. Suda. Source-adaptive multi-layered multicast algorithms for real-time video distribution. IEEE/ACM Transactions on Networking, December 2000.
Jiann-Jone Chen and D.W. Lin. Optimal bit allocation for coding of video signals over ATM networks. IEEE Journal on Selected Areas in Communications, 15(6): 1002–1015, August 1997.
Po-Yuen Cheng, Jin Li, and Jay Kuo. Rate control for an embedded wavelet video coder. IEEE Transactions on Circuits and Systems for Video Technology, 7(4):696–702, August 1997.
Chun-Ting Chou and Kang Shin. Analysis of combined adaptive bandwidth allocation and admission control in wireless networks. In Proceedings of IEEE Infocom, 2002.
Sergey Gorinsky, K. K. Ramakrishnan, and Harrick Vin. Addressing heterogeneity and scalability in layered multicast congestion control. Technical report. Department of Computer Sciences, The University of Texas at Austin, 2000.
Sergey Gorinsky and Harrick Vin. The utility of feedback in layered multicast congestion control. In Proceedings of NOSSDAV, 2001.
Zhihai He, Jianfei Cai, and Chang Wen Chen. Joint source channel rate-distortion analysis for adaptive mode selection and rate control in wireless video coding. IEEE Transactions on Circuits and Systems for Video Technology, 12(6):511–523, June 2002.
Koushik Kar, Saswati Sarkar, and Leandros Tassiulas. Optimization based rate control for multirate multicast sessions. Technical report. Institute of Systems Research and University of Maryland, 2000.
A. Ortega and K. Ramchandran. Rate-distortion methods for image and video compression. IEEE Signal Processing Magazine, November 1998.
Serge Plotkin. Competitive routing of virtual circuits in ATM networks. JSAC, 13(6):1128–1136, 1995.
K. Ramchandran, A. Ortega, and M. Vetterli. Bit allocation for dependent quantization with applications to multiresolution and MPEG video coders. IEEE Transactions on Image Processing, 3:533–545, September 1994.
Reza Rejaie, Mark Handley, and Deborah Estrin. Quality adaptation for congestion controlled video playback over the internet. In SIGCOMM, pages 189–200, 1999.
Despina Saparalla and Keith Ross. Optimal streaming of layered video. In Proceedings of Infocom, 2000.
Guido Schuster and A. K. Katsaggelos. Rate-Distortion Based Video Compression; Optimal Video Frame Compression and Object Boundary Encoding. Kluwer Academic Publishers, 1997.
Gary Sullivan and Thomas Wiegand. Rate-distortion optimization for video compression. IEEE Signal Processing Magazine, November 1998.
Jean Walrand. An introduction to queueing networks. Prentice Hall, 1988.
Steven Weber and Gustavo de Veciana. Asymptotic analysis of rate adaptive multimedia streams. In G. Anandalingam and S. Raghaven, editors. Telecommunications Network Design and Management. Kluwer Academic Publishers, 2003.
Steven Weber and Gustavo de Veciana. Network design for rate adaptive multimedia streams. In IEEE Infocom, 2003.
Steven Weber and Gustavo de Veciana. Rate adaptive multimedia streams: Optimization, admission control, and distributed algorithms, submitted to IEEE Transactions on Networking, 2004.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer Science+Business Media, Inc.
About this paper
Cite this paper
Weber, S., de Veciana, G. (2006). Multiple Service Classes for Rate Adaptive Streams. In: Raghavan, S., Anandalingam, G. (eds) Telecommunications Planning: Innovations in Pricing, Network Design and Management. Operations Research/Computer Science Interfaces Series, vol 33. Springer, Boston, MA. https://doi.org/10.1007/0-387-29234-9_18
Download citation
DOI: https://doi.org/10.1007/0-387-29234-9_18
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-29222-9
Online ISBN: 978-0-387-29234-2
eBook Packages: Business and EconomicsBusiness and Management (R0)