Abstract
Admission control software is used to make accept or deny decisions about incoming service requests to avoid overload. Existing media streaming software includes only limited support for admission control by allowing for predefined static rules. Such rules limit for example the number of requests that are allowed to enter the system during a certain time or define thresholds concerning the utilization level of a single resource such as network bandwidth. In media streaming applications, however, the bottleneck resource (CPU, Disk I/O, network bandwidth, etc.) might change over time depending on the current demand for different types of audio or video files. This paper proposes a model for adaptive admission control in the presence of multiple scarce resources. Opportunity costs for a service request are determined at the moment of an incoming request and compared to the revenue of a request in order to make an accept/deny decision. Opportunity costs are based on resource utilization, service resource requirements, expected future demand for services, and the revenue per accepted service. The model allows rejection of service requests early to reserve capacity required to perform future service requests with higher revenues. We describe a number of experiments to illustrate the benefits of adaptive admission control models over static admission control rules.
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References
Frost&Sullivan (2005) World media streaming platform markets. Frost & Sullivan, Palo Alto, USA
Cherkasova L, Tang W, Vahdat A (2004) MediaGuard: a model-based framework for building QoS-aware streaming media services. HP Labs Report No. HPL-2004-25
Cherkasova L, Staley L (2003) Measuring the capacity of a streaming media server in a utility data center environment. Internet Systems and Storage Laboratory, HP Laboratories, Palo Alto, USA
OGC (2002) ITIL best practice for service delivery 4th edn. The Stationary Office, Norwich
OGC (2003) IT Infrastructure Library (ITIL). [World Wide Web Resource, cited 2005 2005-09-18]; Available from: http://www.itil.co.uk/
Xia Z et al (2006) An integrated admission control scheme for the delivery of streaming media. J Parallel Distrib Comput 66(3):334–344
Yubing Wang MC, Zheng Zuo (2001) An empirical study of realvideo performance across the Internet. In: ACM SIGCOMM internet measurement workshop, San Francisco, USA
Kim RY, Manas T, Pramod KSU (2005) Policy-based admission control and bandwidth reservation for future sessions. European Patent Office
Vin H, Goyal A, Goyal P (1994) A statistical admission control algorithm for multimedia servers. In: International multimedia conference, San Francisco, USA
Chen I -R, Chen C -M (1996) Threshold-based admission control policies for multimedia servers. Comput J 39(9):757–766
Cheng S, Chen C, Chen I (2003) Performance evaluation of an admission control algorithm: dynamic threshold with negotiation. Perform Eval 52(1):1–13
Acharya S, et al. (2000) Characterizing user access to videos on the world wide web. In: ACM / SPIE Multimedia Computing and Networking
Almeida JM, et al. (2001) Analysis of educational media server workloads. In: 11th international workshop on network and operating system suport for digital audio and video
Cherkasova L, Gupta M (2002) Characterizing locality, evolution and life span of accesses in enterprise media server workloads. In: 12th international workshop on network and operating system support for digital audio and video ACM NOSSDAV
Chen X, Mohapatra P, Chen H (2001) An admission control scheme for predictable server response time for web accesses. In: World Wide Web conference
Wang Y, Claypool M, Zuo Z (2001) An empirical study of realvideo performance across the Internet. In: ACM SIGCOMM internet measurement workshop, San Francisco, USA
Ge Z, Ping J, Shenoy P (2002) A demand adaptive and locality aware (DALA) streaming media server cluster architecture. In: International workshop on network and operating system support for digital audio and video. Miami, USA
Cherkasova L, Staley L (2003) Building a performance model of streaming media applications in utility data center environments. In: International symposium on cluster computing and the grid (IEEE Computer Society)
Apple Computer (2003) QuickTime streaming server 5.0 administration. Apple Computer, Inc
RealNetworks (2005) Helix server administration guide [cited 2006 September, 26, available from: http://service.real.com/help/library/guides/HelixServerWireline/wwhelp/wwhimpl/js/html/wwhelp.htm
Microsoft (2006) Windows media services 9 series [cited 2006 September, 12] available from: http://www.microsoft.com/windows/windowsmedia/forpros/server/server.aspx
Adobe (2006) Flash media server 2 documentation [cited 2006 September, 15] available from: http://download.macromedia.com/pub/documentation/en/flashmediaserver/2/fms_pdfs.zip
Kwon J, Yeom H (2000) An admission control scheme for continuous media servers using caching. In: Int’l performance, computing and communication conference (IPCCC), Phoenix, USA
Vin HM, Goyal A, Goyal P (1994) An observation-based admission control algorithm for multimediaservers. In: Multimedia computing and systems, Boston, USA
Welsh M, Culler D, Brewer E (2001) SEDA: An architecture for well-conditioned, scalable Internet services. In: 18th symposium on operating systems principles, Chateau Lake Louise, Canada
Welsh M, Culler D (2003) Adaptive overload control for busy internet servers. In: 4th usenix conference on internet technologies and systems (USITS)
Welsh M, Culler D (2002) Overload management as a fundamental service design primitive. In: Tenth ACM SIGOPS European workshop, Saint-Emilion, France
Williamson (1992) Airline network seat inventory control—methodologies and revenue impacts. In: Department of Aeronautics and Astronautics, MIT, USA
Talluri KT, van Ryzin GJ (1999) An analysis of bid-price controls for network revenue management. Manage Sci 44:1577–1593
Brandl R (2006) Reinraum-Messungen zur Verrechnung von IT-Anwendungen. In: Multikonferenz Wirtschaftsinformatik, Passau, Germany
Nagaprabhanjan B, Apte V (2005) A tool for automated resource consumption profiling of distributed transactions. In: Second international conference, ICDCIT, Bhubaneswar, India
Kounev S, Buchmann A (2003) Performance modelling and evaluation of large-scale J2EE applications. In: 29th international conference of the computer measurement group (CMG)
Microsoft (2006) Windows media load simulator for windows media services 9 series. [cited 2006 Oktober, 9] available from: http://www.microsoft.com/windows/windowsmedia/forpros/serve/tools.aspx
Yu H, et al. (2006) Understanding user behavior in large-scale video-on-demand systems. In: EuroSys
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Bichler, M., Setzer, T. Admission control for media on demand services. SOCA 1, 65–73 (2007). https://doi.org/10.1007/s11761-007-0005-0
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DOI: https://doi.org/10.1007/s11761-007-0005-0