Network Coding Enabled Delay-Sensitive Multi-Party Video Conferencing

We have two works to revisit the problem of multi-party conferencing and rethink the design space beyond those explored in existing solutions which led by Prof. Minghua Chen.


1. Celerity: A Low Delay Multiparty Conferencing Solution

We present "Celerity: A Low Delay Multiparty Conferencing Solution" [1,2], a multi-party conferencing solution specifically designed to maximizing session rate, while being subjected to a tight end-to-end delay constraints between any two parties which makes the problem uniquely challenging. 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 apply network coding to allow flexible and opportunistic local loss recovery, without incurring additional retransmission delay which deteriorates conferencing experience. We have implemented Celerity in a prototype system, and demonstrate its superior performance over existing industrial and academic solutions, including Skype, in a local experimental testbed and over the Internet.

2. Cost-Effective Low-Delay Cloud Video Conferencing

As cloud computing paradigm has been advocated in recent video conferencing system design, we present our second work "Cost-Effective Low-Delay Cloud Video Conferencing" [
3] to exploit the rich on-demand resources of a distributed cloud for better conferencing experience. A typical architectural design in cloud environment is to create video conferencing agents, i.e., virtual machines, in each cloud site, assign users to the agents, and enable inter-user communication through the agents. Given the diversity of devices and network connectivities of the users, the agents may also transcode the conferencing streams to the best formats and bitrates. In this architecture, two key issues exist on how to effectively assign users to agents and how to identify the best agent to perform a transcoding task, which are nontrivial due to the following: (1) the existing proximity-based assignment may not be optimal in terms of inter-user delay, which fails to consider the whereabouts of the other users in a conferencing session; (2) the agents may have heterogeneous bandwidth and processing availability, such that the best transcoding agents should be carefully identified, for cost minimization while best serving all the users requiring the transcoded streams.

To address these challenges, we formulate the user-to-agent assignment and transcoding-agent selection problems as an optimization problem, which targets at minimizing the operational cost of the conferencing provider while keeping the conferencing delay low. Using the recently-proposed Markov approximation framework of tackling combinatorial problems, we design a decentralized algorithm that provably converges to a bounded neighborhood of the optimal solution and adapts to system dynamics. An agent ranking scheme is also proposed to properly initialize our algorithm so as to improve its convergence. We implement a prototype video conferencing system realizing our algorithms, and carry out extensive evaluations using real-world traces. In a set of Internet-scale scenarios, our design reduces the operational cost by 77% as compared to a commonly-adopted alternative, while simultaneously yielding lower conferencing delays. Applying network coding to allow loss recovery is one of our future works.


[1] Xiangwen Chen, Minghua Chen, Baochun Li, Yao Zhao, Yunnan Wu, and Jin Li.
"Celerity: a low-delay multi-party conferencing solution."
Proceedings of the 19th ACM international conference on Multimedia, pp. 493-502, 2011 [PDF[Technical Report]

[2] Xiangwen Chen, Minghua Chen, Baochun Li, Yao Zhao, Yunnan Wu, and Jin Li.
"Celerity: A Low-Delay Multi-Party Conferencing Solution."
IEEE Journal on Selected Areas in Communications, vol.31, no.9, pp.155,164, September 2013 [PDF]

[3] Mohammad H. Hajiesmaili, Lok To Mak, Zhi Wang, Chuan Wu, Minghua Chen, and Ahmad Khonsari.
"Cost-Effective Low-Delay Cloud Video Conferencing."
Proceedings of the 35th IEEE International Conference on Distributed Computing Systems, 2015 [PDF]