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General Principles of Intellectual Property: Concepts of Intellectual Proper...
COST-EFFECTIVE LOW-DELAY DESIGN FOR MULTI-PARTY CLOUD VIDEO CONFERENCING
1. CONTACT: PRAVEEN KUMAR. L (,+91 – 9791938249)
MAIL ID: , praveen@nexgenproject.com
Web: www.nexgenproject.com,
COST-EFFECTIVE LOW-DELAY DESIGN FOR MULTI-PARTY CLOUD
VIDEO CONFERENCING
ABSTRACT
Multi-party cloud video conferencing architecturehas been recently advocated to exploit rich
computing andbandwidth resources in cloud to effectively improve video
conferencingperformance. As a typical design in this architecture,multiple agents, i.e., virtual
machines, are deployed in differentcloud sites, and users are assigned to the agents. Then,
theusers communicate through the agents, and the agents mighttranscode the recorded videos
given the heterogeneities amongdevices in terms of hardware specification and connectivity.
Inthis architecture, two critical and nontrivial challenges are: (1)assigning users to agents to
reduce the operational cost andthe user-to-user conferencing delay, (2) identifying best agentsto
perform transcoding tasks, taking into account the heterogeneousbandwidth and processing
availabilities. To address thesechallenges, we cast a joint problem of user-to-agent
assignmentand transcoding-agent selection. The ultimate objective is tosimultaneously minimize
the cost of the service provider andthe conferencing delay. The problem is combinatorial in
naturewhich belongs to the NP-hard node assignment problems. Weleverage the Markov
approximation framework and devise anadaptive parallel algorithm that finds a close-to-optimal
solutionto our problem with a bounded performance guarantee. Toevaluate the performance of
our solution, we implement aprototype video conferencing system, and carry out trace-
drivenexperiments. In a set of large-scale experiments using PlanetLabtraces, our solution
decreases the operational cost by 77% andsimultaneously yields lower conferencing delay
compared to anexisting alternative.
2. CONTACT: PRAVEEN KUMAR. L (,+91 – 9791938249)
MAIL ID: , praveen@nexgenproject.com
Web: www.nexgenproject.com,
EXISTING SYSTEM:
Multi-party Video Conferencing. Previously, P2P architecture was considered as an alternative
to traditionalclient/server architecture. In , following network utilitymaximization framework, a
problem of video conferencingin P2P architecture has been studied. In another recent work the
authors propose a scheme to maximize video qualityunder uplink-downlink capacity constraints
for peer-to-peermulti-party video conferencing. However, in P2P there is nopowerful server in
the architecture which hinders executing thehigh demand tasks such as transcoding. The cloud
architecturefor video conferencing has been proposed in Airlift [19] forthe first time, and it
suggests to use cloud bandwidth resourcesto boost the conferencing experience. In vSkyConf
thecomputational resources of the cloud is exploited for executingprocessing tasks, in addition to
the dedicated cloud communicationinfrastructure. These studies assume nearest
assignmentpolicy, which is not optimal in a multi-party applicationin terms of intra-cloud traffic
and user-to-user conferencingdelay. Two recent studiespropose different
serverselection/placement and topology control approaches to onlyminimize the latency in
transcoding-free video conferencing,without taking into account the operational cost. Finally,the
delay-constrained video streaming in different networkinfrastructures and applications has been
studied previously,e.g., in wireless and wireline networks
PROPOSED SYSTEM:
Almost all of the existing studies that we are aware,neglect to consider the cost to the service
provider andsimply adopt the nearest policy for user-to-agent assignment. To the best of
ourknowledge, this study is the first that aims to improve the cloudvideo conferencing design by
tackling the user-to-agent andtranscoding assignments problem in a unified
combinatorialoptimization framework. The main contributions of this studyare summarized
below.B We formulate the User-to-agent Assignment Problem(UAP), that tries to select the user-
3. CONTACT: PRAVEEN KUMAR. L (,+91 – 9791938249)
MAIL ID: , praveen@nexgenproject.com
Web: www.nexgenproject.com,
to-agent assignment andtranscoding assignment in a multi-party application with theobjective of
simultaneously minimizing the operational cost tothe service provider and conferencing delay.
The problem issubject to the capacity constraints of the diverse agents and theuser-to-user
conferencing delay constraints. The problem is anonlinear combinatorial optimization problem in
the categoryof NP-hard node assignment problems which are difficultto solve due to persistent
dynamics in the system and largeproblem size.B We leverage the Markov approximation
framework which is a technique for solving the combinatorial networkproblems in a distributed
fashion. We devise an efficientparallel and iterative algorithm to solve the UAP, which
runslocally in a representative agent of each session and convergesto a close-to optimal
assignment. The algorithm adapts to thesystem dynamics, provides a bounded approximation
gap, andis robust against the inaccurate measurements of the problemdata. In addition, we
improve the convergence of the algorithmby proposing another initialization algorithm called
AgRank,which is a simple scheme with low complexityWe implement a cloud video
conferencing system prototypeusing Amazon EC2 platform and also carry out
tracedrivenevaluation experiments using PlanetLab nodes. Theresults demonstrate the significant
improvement of our solutioncompared to the existing alternatives. In a representative
experimentalsetting of PlanetLab traces, our algorithm outperformsthe nearest assignment policy
by reducing theoperational cost and the delay by 77% and 2%, respectively
CONCLUSIONS AND FUTURE DIRECTIONS
This study addresses the problem of user-to-agent assignmentand transcoding task assignment in
cloud videoconferencing architecture. Considering the challenges of theproblem due to the
underlying large-scale combinatorial problem,we devise a parallel and adaptive solution to
optimizethe assignment tasks. The algorithm achieves a suboptimalsolution with a bounded
performance guarantee. Observationson prototype system implementation corroborate our claim
thatuser assignment is a critical design issue in cloud architecturethat can lead to a big difference
4. CONTACT: PRAVEEN KUMAR. L (,+91 – 9791938249)
MAIL ID: , praveen@nexgenproject.com
Web: www.nexgenproject.com,
in entire system performance.In addition, trace-driven simulations demonstrate that oursolution
design outperforms the existing solutions in terms ofreduced delay and cost, and thus
demonstrates its viability asa win-win solution for both users and conferencing servicengbr
provider. Finally, in future research, a promising directionto tackle is the more general problem
in which other tasks,rather than transcoding are performed at the cloud agents. Theproblem could
be further generalized to consider other types ofcommunication and computation cloud resources
for generalinteractive real-time multimedia applications.ACKNOWLEDGMENTThe work
presented in this paper was supported in partby National Basic Research Program of China
(Project No.2013CB336700) and the University Grants Committee of theHong Kong Special
Administrative Region, China (Area ofExcellence Grant Project No. AoE/E-02/08 and
CollaborativeResearch Fund No. C7036-15G), and the National NaturalScience Foundation of
China under Grant No. 61402247, andHong Kong RGC grants 718513, 17204715, and
17225516.
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5. CONTACT: PRAVEEN KUMAR. L (,+91 – 9791938249)
MAIL ID: , praveen@nexgenproject.com
Web: www.nexgenproject.com,
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