Asymptotic behavior of global recovery in SRM

  • Authors:
  • Suchitra Raman;Steven McCanne;Scott Shenker

  • Affiliations:
  • University of California, Berkeley;University of California, Berkeley;Xerox Palo Alto Research Center

  • Venue:
  • SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
  • Year:
  • 1998

Quantified Score

Hi-index 0.00

Visualization

Abstract

The development and deployment of a large-scale, wide-area multicast infrastructure in the Internet has enabled a new family of multi-party, collaborative applications. Several of these applications, such as multimedia slide shows, shared whiteboards, and large-scale multi-player games, require reliable multicast transport, yet the underlying multicast infrastructure provides only a best-effort delivery service. A difficult challenge in the design of efficient protocols that provide reliable service on top of the best-effort multicast service is to maintain acceptable performance as the protocol scales to very large session sizes distributed across the wide area. The Scalable, Reliable Multicast (SRM) protocol [6] is a receiver-driven scheme based on negative acknowledgments (NACKs) reliable multicast protocol that uses randomized timers to limit the amount of protocol overhead in the face of large multicast groups, but the behavior of SRM at extremely large scales is not well-understood.In this paper, we use analysis and simulation to investigate the scaling behavior of global loss recovery in SRM. We study the protocol's control-traffic overhead as a function of group size for various topologies and protocol parameters, on a set of simple, representative topologies --- the cone (a variant of a clique), the linear chain, and the binary tree. We find that this overhead, as a function of group size, depends strongly on the topology: for the cone, it is always linear; for the chain, it is between constant and logarithmic; and for the tree, it is between constant and linear.