Celerity: A Low-Delay Multi-Party Conferencing Solution

In this paper, we revisit the problem of multi-party conferencing from a practical perspective, and to rethink the design space involved in this problem. We believe that an emphasis on low end-to-end delays between any two parties in the conference is a must, and the source sending rate in a session should adapt to bandwidth availability and congestion. We present Celerity, a multi-party conferencing solution specifically designed to achieve our objectives. It is entirely Peer-to-Peer (P2P), and as such eliminating the cost of maintaining centrally administered servers. It is designed to deliver video with low end-to-end delays, at quality levels commensurate with available network resources over arbitrary network topologies where bottlenecks can be anywhere in the network. This is in contrast to commonly assumed P2P scenarios where bandwidth bottlenecks reside only at the edge of the network. The highlight in our design is a distributed and adaptive rate control protocol, that can discover and adapt to arbitrary topologies and network conditions quickly, converging to efficient link rate allocations allowed by the underlying network. In accordance with adaptive link rate control, source video encoding rates are also dynamically controlled to optimize video quality in arbitrary and unpredictable network conditions. We have implemented Celerity in a prototype system, and demonstrate its superior performance over existing solutions in a local experimental testbed and over the Internet.

[1]  Yao Zhao,et al.  Celerity: towards low-delay multi-party conferencing over arbitrary network topologies , 2011, NOSSDAV '11.

[2]  Yong Liu,et al.  Optimal Bandwidth Sharing in Multiswarm Multiparty P2P Video-Conferencing Systems , 2011, IEEE/ACM Transactions on Networking.

[3]  Jean C. Walrand,et al.  Fair end-to-end window-based congestion control , 2000, TNET.

[4]  László Lovász,et al.  On two minimax theorems in graph , 1976, J. Comb. Theory, Ser. B.

[5]  Frank Kelly,et al.  Fairness and Stability of End-to-End Congestion Control , 2003, Eur. J. Control.

[6]  Öznur Özkasap,et al.  Peer-to-Peer Multipoint Video Conferencing using Layered Video , 2006, 2006 International Conference on Image Processing.

[7]  Angelia Nedic,et al.  Subgradient Methods for Saddle-Point Problems , 2009, J. Optimization Theory and Applications.

[8]  Anees Shaikh,et al.  An empirical evaluation of wide-area internet bottlenecks , 2003 .

[9]  Ronald E. Bruck On the weak convergence of an ergodic iteration for the solution of variational inequalities for monotone operators in Hilbert space , 1977 .

[10]  S. Low,et al.  Understanding Vegas: a duality model , 2002 .

[11]  Yunnan Wu,et al.  Distributed Utility Maximization for Network Coding Based Multicasting: A Critical Cut Approach , 2006, 2006 4th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks.

[12]  Liang Guo,et al.  QDMR: An efficient QoS dependent multicast routing algorithm , 2000, Journal of Communications and Networks.

[13]  Minghua Chen,et al.  Utility maximization in peer-to-peer systems , 2008, SIGMETRICS '08.

[14]  Minghua Chen,et al.  Multi-rate peer-to-peer video conferencing: A distributed approach using scalable coding , 2009, 2009 IEEE International Conference on Multimedia and Expo.

[15]  Jia Wang,et al.  Locating internet bottlenecks: algorithms, measurements, and implications , 2004, SIGCOMM 2004.

[16]  Steven H. Low,et al.  Understanding TCP Vegas: a duality model , 2002 .

[17]  Yao Zhao,et al.  Celerity: A Low-Delay Multi-Party Conferencing Solution , 2011, IEEE Journal on Selected Areas in Communications.

[18]  Minghua Chen,et al.  Optimizing Multi-Rate Peer-to-Peer Video Conferencing Applications , 2011, IEEE Transactions on Multimedia.