Title
CoolConferencing: Enabling Robust Peer-to-Peer Multi-Party Video Conferencing.
Abstract
Multi-party video conferencing (MPVC) is the next big opportunity for Internet streaming. Commercial MPVC solutions are either server-based or peer-to-peer (P2P)-based, which both have performance limitations. P2P technology is expected to dominate the MPVC platform. There are four requirements for a robust MPVC system: 1) realistic network assumptions; 2) realistic system settings; 3) multi-rate support; and 4) any-view support. Existing academic works study the problem from a theoretical perspective, and none of them meets all four requirements simultaneously. We design CoolConferencing, an overlay network for robust P2P MPVC. The core operations follow the easy-to-implement, robust, and resilient data-driven principle, which does not maintain complex global structures such as dissemination trees and can adapt to network dynamic distributedly and quickly. CoolConferencing is a robust system that meets all four requirements simultaneously. In addition, to the best of our knowledge, there is no existing work which examines its MPVC approach under various realistic network environments. We have evaluated CoolConferencing via an event-driven simulation. Compared with state-of-the-art video conferencing solutions, CoolConferencing achieves around 25% gain than Mutualcast and around 9% gain than Celerity in performance. Moreover, when the helper mechanism is enabled, CoolConferencing can easily exploit all available bandwidth to get optimal video transmission performance.
Year
DOI
Venue
2017
10.1109/ACCESS.2017.2768798
IEEE ACCESS
Keywords
Field
DocType
Computer networks,streaming media,peer to peer computing
Peer-to-peer,Computer science,Computer network,Exploit,Robustness (computer science),Video transmission,Bandwidth (signal processing),Videoconferencing,Overlay network,The Internet
Journal
Volume
ISSN
Citations 
5
2169-3536
1
PageRank 
References 
Authors
0.37
29
6
Name
Order
Citations
PageRank
Weimin Wu123643.97
Hanzi Mao210.37
Yi Wang33514.57
Ji Wang410.37
Wenkai Wang510.37
Chen Tian6111984.93