Controlling smoothness and loss rate for elastic continuous media flows

The class of rate adaptation schemes based on linear loss dependent decrease (LDD) policies is considered. A particular LDD policy, referred to as the history independent (hi)-LDD policy, is identified and studied here and some interesting properties are shown. Based on these properties it is possible to estimate the fair share and use it to adjust dynamically the control parameters so that a given targeted level of smoothness and loss rate be achieved; this policy is referred to as the Dynamic hi-LDD policy. Rate adaptation schemes based on the introduced Dynamic hi-LDD policy are suitable for elastic continuous media (CM) flows since they provide for a smooth rate adaptation and low packet loss rates. Numerical results illustrate the good properties and intrinsic advantages of the investigated schemes.

[1]  Avideh Zakhor,et al.  Real-Time Internet Video Using Error Resilient Scalable Compression and TCP-Friendly Transport Protocol , 1999, IEEE Trans. Multim..

[2]  Henning Schulzrinne,et al.  Dynamic QoS control of multimedia applications based on RTP , 1996, Comput. Commun..

[3]  Sethuraman Panchanathan,et al.  Traffic and Quality Characterization of Scalable Encoded Video : A Large-Scale Trace-Based Study Part 2 : Statistical Analysis of Single-Layer Encoded Video ∗ † , .

[4]  Ioannis Stavrakakis,et al.  A Multi-state Congestion Control Scheme for Rate Adaptable Unicast Continuous Media Flows , 2001, IWDC.

[5]  David L. Black,et al.  An Architecture for Differentiated Service , 1998 .

[6]  Songwu Lu,et al.  Improving congestion control performance through loss differentiation , 1999, Proceedings Eight International Conference on Computer Communications and Networks (Cat. No.99EX370).

[7]  Ioannis Stavrakakis,et al.  A self-adjusting rate adaptation scheme with good fairness and smoothness properties , 2005, Comput. Networks.

[8]  Hayder Radha,et al.  Increase-decrease congestion control for real-time streaming: scalability , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[9]  Zheng Wang,et al.  An Architecture for Differentiated Services , 1998, RFC.

[10]  Adam Wolisz,et al.  MLDA: a TCP-friendly congestion control framework for heterogeneous multicast environments , 2000, 2000 Eighth International Workshop on Quality of Service. IWQoS 2000 (Cat. No.00EX400).

[11]  Henning Schulzrinne,et al.  The Loss-delay Based Adjustment Algorithm: a Tcp-friendly Adaptation Scheme , 1998 .

[12]  Thierry Turletti,et al.  Experience with control mechanisms for packet video in the internet , 1998, CCRV.

[13]  Sally Floyd,et al.  Promoting the use of end-to-end congestion control in the Internet , 1999, TNET.

[14]  Raj Jain,et al.  Analysis of the Increase and Decrease Algorithms for Congestion Avoidance in Computer Networks , 1989, Comput. Networks.

[15]  W. Richard Stevens,et al.  TCP Slow Start, Congestion Avoidance, Fast Retransmit, and Fast Recovery Algorithms , 1997, RFC.

[16]  Deborah Estrin,et al.  RAP: An end-to-end rate-based congestion control mechanism for realtime streams in the Internet , 1999, IEEE INFOCOM '99. Conference on Computer Communications. Proceedings. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. The Future is Now (Cat. No.99CH36320).

[17]  Henning Schulzrinne,et al.  RTP: A Transport Protocol for Real-Time Applications , 1996, RFC.

[18]  Scott Shenker,et al.  Fundamental Design Issues for the Future Internet (Invited Paper) , 1995, IEEE J. Sel. Areas Commun..

[19]  S. Shenker Fundamental Design Issues for the Future Internet , 1995 .