Towards Self-organizing Distribution Structures for Streaming Media

  • Hans Ole Rafaelsen
  • Frank Eliassen
  • Sharath Babu Musunoori
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4276)


Efficient multi-receiver delivery of video data over computer networks, such as the Internet is still challenging, due to heterogeneity in involved network technologies, end-node capabilities and receiver preferences. While adaptive and scalable video encoding can solve many of the problems caused by heterogeneity, media gateway systems are needed for performing video filtering and transformation in order to handle cases not solved by scalable coding. The complexity of such systems makes them difficult to manage by humans. Hence streaming media delivery systems, including media gateway systems should be self-managed only guided by policies provided by system managers and users.

In this paper, we describe a media gateway systems framework for developing binding managers for gateway-based stream bindings. These bindings construct an overlay network for media stream distribution. The framework is open, enabling insertion of specific binding policies that suits particular user preferences. Our framework contributes towards self-management of multi-user streaming services by supporting self-configuration and re-configuration of multi-receiver bindings. It also contributes to easier development of business streaming applications by supporting the plugging in of binding policies targeting particular application domains. We describe the implementation of a prototype of the framework and evaluate the framework by observing and comparing the effect on the property of bindings when different binding policies are applied. Finally we discuss issues of gateway service placement when bindings are deployed in a large scale infrastructure.


Steiner Tree Overlay Network Vehicle Rout Problem Multicast Tree Media Stream 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Hans Ole Rafaelsen
    • 1
  • Frank Eliassen
    • 1
  • Sharath Babu Musunoori
    • 1
  1. 1.Simula Research LaboratoryLysakerNorway

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