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Cost-Effective Low-Delay Cloud Video Conferencing

  • Mohammad H. Hajiesmaili
  • , Lok To Mak
  • , Zhi Wang
  • , Chuan Wu
  • , Minghua Chen
  • , Ahmad Khonsari

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

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.
Original languageEnglish
Title of host publicationProceedings - 2015 IEEE 35th International Conference on Distributed Computing Systems, ICDCS 2015
PublisherIEEE
Pages103-112
ISBN (Print)9781467372145
DOIs
Publication statusPublished - Jun 2015
Externally publishedYes
Event35th IEEE International Conference on Distributed Computing Systems (ICDCS 2015) - Columbus, United States
Duration: 29 Jun 20152 Jul 2015

Publication series

NameProceedings - International Conference on Distributed Computing Systems
Volume2015-July
ISSN (Print)1063-6927

Conference

Conference35th IEEE International Conference on Distributed Computing Systems (ICDCS 2015)
PlaceUnited States
CityColumbus
Period29/06/152/07/15

Research Keywords

  • Cloud Computing
  • Combinatorial Network Problem
  • Parallel Algorithm
  • Video Conferencing

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