Cost-Effective Low-Delay Cloud Video Conferencing

• Main Authors: Hajiesmaili, Mohammad H., Lok To Mak, Zhi Wang, Chuan Wu, Minghua Chen, Khonsari, Ahmad
• Format: Conference Proceeding
• Language: English
• Subjects: Algorithms; Approximation algorithms; Approximation methods; Bandwidth; Cloud Computing; Combinatorial Network Problem; Cost engineering; Delay; Delays; Design engineering; Distributed processing; Heuristic algorithms; Markov processes; Optimization; Parallel Algorithm; Transcoding; Video Conferencing; Videoconferencing
• ISSN: 1063-6927; 2575-8411
• DOI: 10.1109/ICDCS.2015.19

The cloud computing paradigm has been advocated in recent video conferencing system design, which exploits the rich on-demand resources spanning multiple geographic regions 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 Transco ding 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 Transco ding 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 Transco ding-agent selection problems, which targets at minimizing the operational cost of the conferencing provider while keeping the conferencing delay low. The optimization problem is combinatorial in nature and difficult to solve. Using Markov approximation framework, we design a decentralized algorithm that provably converges to a bounded neighborhood of the optimal solution. An agent ranking scheme is also proposed to properly initialize our algorithm so as to improve its convergence. The results from a prototype system implementation show that our design in a set of Internet-scale scenarios reduces the operational cost by 77% as compared to a commonly-adopted alternative, while simultaneously yielding lower conferencing delays.