Dagstream: Locality aware and failure resilient peer-to-peer streaming

Jin Liang, Klara Nahrstedt

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Live peer to peer (P2P) media streaming faces many challenges such as peer unreliability and bandwidth heterogeneity. To effectively address these challenges, general "mesh" based P2P streaming architectures have recently been adopted. Mesh-based systems allow peers to aggregate bandwidth from multiple neighbors, and dynamically adapt to changing network conditions and neighbor failures. However, a drawback of mesh-based overlays is that it is difficult to guarantee network connectivity in a distributed fashion, especially when network locality needs to be optimized. This paper introduces a new P2P streaming framework called DagStream, which (1) organizes peers into a directed acyclic graph (DAG) where each node maintains at least k parents, thus has provable network connectivity (and hence failure resilience), and (2) enables peers to quickly achieve locality awareness in a distributed fashion, thus ensures efficient network resource usage. Our experiment results in both simulation and wide area environment show that with our DagStream protocol, peers can quickly self-organize into a locality aware DAG. Further, by selecting additional parents as needed, peers can achieve good streaming quality commensurate with their downlink bandwidth.

Original languageEnglish (US)
Title of host publicationMultimedia Computing and Networking 2006 - Proceedings of SPIE-IS and T Electronic Imaging
StatePublished - 2006
EventMultimedia Computing and Networking 2006 - San Jose, CA, United States
Duration: Jan 18 2006Jan 19 2006

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


OtherMultimedia Computing and Networking 2006
Country/TerritoryUnited States
CitySan Jose, CA

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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