The dynamic and stochastic knapsack problem with deadlines
Management Science
Quality adaptation for congestion controlled video playback over the Internet
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Quantifying Skype user satisfaction
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
Budget constrained bidding in keyword auctions and online knapsack problems
Proceedings of the 17th international conference on World Wide Web
An optimization model for Web content adaptation
Computer Networks: The International Journal of Computer and Telecommunications Networking
The Essential Guide to Video Processing
The Essential Guide to Video Processing
Rate adaptation for adaptive HTTP streaming
MMSys '11 Proceedings of the second annual ACM conference on Multimedia systems
Understanding the impact of video quality on user engagement
Proceedings of the ACM SIGCOMM 2011 conference
An end-to-end adaptation protocol for layered video multicast using optimal rate allocation
IEEE Transactions on Multimedia
IEEE Transactions on Circuits and Systems for Video Technology
TUBE: time-dependent pricing for mobile data
Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication
A case for a coordinated internet video control plane
Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication
Context-aware frame rate adaption for video chat on smartphones
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
A survey of smart data pricing: Past proposals, current plans, and future trends
ACM Computing Surveys (CSUR)
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Two emerging trends of Internet applications, video traffic becoming dominant and usage-based pricing becoming prevalent, are at odds with each other. Given this conflict, is there a way for users to stay within their monthly data plans (data quotas) without suffering a noticeable degradation in video quality? In this work, we develop an online video adaptation system, called Quota Aware Video Adaptation (QAVA), that manages this tradeoff by leveraging the compressibility of videos and by predicting consumer usage behavior throughout a billing cycle. We propose the QAVA architecture and develop its main modules, including Stream Selection, User Profiling, and Video Profiling. Online algorithms are designed through dynamic programming and evaluated using real video request traces. Empirical results suggest that QAVA can provide an effective solution to the dilemma of usage-based pricing of heavy video traffic.