Supporting multi-party voice-over-IP services with peer-to-peer stream processing

  • Authors:
  • Xiaohui Gu;Zhen Wen;Philip S. Yu;Zon-Yin Shae

  • Affiliations:
  • IBM T. J. Watson Research Center, Hawthorne, NY;IBM T. J. Watson Research Center, Hawthorne, NY;IBM T. J. Watson Research Center, Hawthorne, NY;IBM T. J. Watson Research Center, Hawthorne, NY

  • Venue:
  • Proceedings of the 13th annual ACM international conference on Multimedia
  • Year:
  • 2005

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Abstract

Multi-party voice-over-IP (MVoIP) services provide economical and natural group communication mechanisms for many emerging applications such as on-line gaming, distance collaboration, and tele-immersion. In this paper, we present a novel peer-to-peer (P2P) stream processing system called peerTalk to provide resource-efficient and failure-resilient MVoIP services. Different from previous work, our solution is fully distributed and self-organizing without requiring specialized servers or IP multicast support. Particularly, we decouple the stream processing in MVoIP services into two phases: (1) aggregation phase that mixes audio streams from active speakers into a single stream; and (2) distribution phase that distributes the mixed audio stream to all listeners. The decoupled model allows us to optimize and adapt the P2P stream mixing and distribution processes separately. Specifically, we can adaptively spread stream mixing workload among resource-constrained peer hosts according to current speaking activities. We have implemented a prototype of the peerTalk system and conducted experiments in real-world wide-area networks. The results show that peerTalk can achieve lower resource contention and better service quality than previous common solution.