Performability Analysis of an Adaptive-Rate Video-Streaming Service in End-to-End QoS Scenarios

  • I. V. Martín
  • J. J. Alins
  • Mónica Aguilar-Igartua
  • Jorge Mata-Díaz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3775)


Nowadays, dynamic service management frameworks are proposed to ensure end-to-end QoS. To achieve this goal, it is necessary to manage Service Level Agreements (SLAs), which specify quality parameters of the services operation such as availability and performance. This work is focused on the evaluation of Video-on-Demand (VoD) services in end-to-end QoS scenarios. Based on a straightforward Markov Chain, Markov-Reward Chain (MRC) models are developed in order to obtain various QoS measures of an adaptive VoD service. The MRC model has a clear understanding with the design and operation of the VoD system. In this way, new design options can be proposed and be easily evaluated. To compute performability measures of the MRC model, the randomization method is employed. Predicted model results fit well to the ones taken from a real video-streaming testbed.


Video Sequence Network Resource Service Level Agreement Video Server Video Source 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Wu, D., Hou, Y., Zhu, W., Zhang, Y., Peha, J.: Streaming Video over Internet: Approaches and Directions. IEEE Trans. On Circuits and Systems for Video Technology 11 (2001)Google Scholar
  2. 2.
    Ghanbari, M.: Video Coding: An Introduction to Standard Codecs. IEE Telecommunications Series, vol. 42. IEEE Publishing, Los Alamitos (1999)Google Scholar
  3. 3.
    De la Cruz, L.J., Mata, J.: Performance of Dynamic Resource Allocation with QoS Guarantees for MPEG VBR Video Traffic Transmission over ATM Networks. In: Proceedings of the IEEE GLOBECOM 1999. IEEE Communications Society, Los Alamitos (1999)Google Scholar
  4. 4.
    Manzoni, P., Cremonesi, P., Serazzi, G.: Workload Models of VBR Traffic and Their Use in Resource Allocation Policies. IEEE/ACM Transactions on Networking 7 (1999)Google Scholar
  5. 5.
    Cortese, G., Cremonese, P., D’Antonio, S., Diaconescu, A., Esposito, M., Fiutem, R., Romano, S.P.: CADENUS: Creation and Deployment of End-User Services in Premium IP Networks. IEEE Communications Magazine (2003)Google Scholar
  6. 6.
    IST Project: TAPAS– Trusted and QoS-Aware Provision of Application Services (2001),
  7. 7.
    Muntean, G., Murphy, L.: A New Adaptive Multimedia Streaming System for All-IP Multi-Service Networks. IEEE Transactions on Broadcasting 50 (2004)Google Scholar
  8. 8.
    Lombardo, A., Schembra, G.: Performance Evaluation of an Adaptive-Rate MPEG Encoder Matching IntServ Traffic Constraints. IEEE/ACM Transactions on Networking 11 (2003)Google Scholar
  9. 9.
    Luna, C., Kondi, L., Katsaggelos, A.: Maximizing User Utility in Video Streaming Applications. IEEE Trans. on Circuits and Systems for Video Technology 13 (2003)Google Scholar
  10. 10.
    Ramanujan, R.S., Newhouse, J., Kaddoura, M., Ahamad, A., Chartier, E., Thurber, K.: Adaptive streaming of MPEG video over IP networks. In: Proceedings 22nd Annual Conference on Local Computer Networks. IEEE, Los Alamitos (1997)Google Scholar
  11. 11.
    Adas, A.: Traffic Models in Broadband Networks. IEEE Communications Magazine 35 (1997)Google Scholar
  12. 12.
    De la Cruz, L.J., Fernàndez, M., Alins, J., Mata, J.: Bidimensional Fluid Model for VBR MPEG Video Traffic. In: 4th International Conference on Broadband Communications, IFIP, TC6/WG6.2. (1998)Google Scholar
  13. 13.
    Martín, I.V., Alins, J., Aguilar-Igartua, M., Mata, J.: Modelling an Adaptive-Rate Video-Streaming Service Using Markov-Rewards Models. In: Proc. of the First International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks (QSHINE 2004). IEEE, Los Alamitos (2004)Google Scholar
  14. 14.
    Meyer, J.: Teletraffic Science for Cost-Effective Systems, Network and Services, ITC-12. In: Performability Evaluation of Telecommunication Network. Elsevier Science Publishers B. V, (North Holland) (1989)Google Scholar
  15. 15.
    Bernet, Y.: RFC 2998: A framework for integrated services operation over diffserv networks (2000)Google Scholar
  16. 16.
    Sarkar, U., Ramakrishnan, S., Sarkar, D.: Study of long-duration MPEG-trace segmentation methods for developing frame-size-based traffic models. In: Computer Networks, vol. 44 (2004)Google Scholar
  17. 17.
    Wu, M., Joyce, R.A., Wong, H., Guan, L., Kung, S.: Dynamic Resource Allocation via Video Content and Short-Term Traffic Statistics. IEEE Transactions on Multimedia 3 (2001)Google Scholar
  18. 18.
    Mashat, A., Kar, M.: Performance Evaluation of a Scene-based Model for VBR MPEG Traffic. Performance Evaluation IFIP WG7.3 36 (1999)Google Scholar
  19. 19.
    Haverkort, B.R., Marie, R., Rubino, G., Trivedi, K.: Performability Modelling. Techniques and Tools. John Wiley & Sons, Chichester (2001)Google Scholar
  20. 20.
    Vallejos, R., Barria, M.: Evaluation of Moments of Cumulative Reward in Reparaible Systems (2005); Submitted to the PERFORMANCE 2005 Conference, Jean le Pins, France Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2005

Authors and Affiliations

  • I. V. Martín
    • 1
  • J. J. Alins
    • 1
  • Mónica Aguilar-Igartua
    • 1
  • Jorge Mata-Díaz
    • 1
  1. 1.Telematics Engineering DepartmentTechnical University of Catalonia (UPC)BarcelonaSpain

Personalised recommendations