ABSTRACT
The exponential growth of media streaming traffic will have a strong impact on the bandwidth consumption of the future wireless infrastructure. One key challenge is to deliver services taking into account the stringent requirements of mobile video streaming, e.g., the users' expected Quality-of-Service. Admission control and resource allocation can strongly benefit from the use of anticipatory information such as the prediction of future user's demand and expected channel gain. In this paper, we use this information to formulate an optimal admission control scheme that maximizes the number of accepted users into the system with the constraint that not only the current but also the expected demand of all users must be satisfied. Together with the optimal set of accepted users, the optimal resource scheduling is derived. In order to have a solution that can be computed in a reasonable time, we propose a low complexity heuristic. Numerical results show the performance of the proposed scheme with respect to the state of the art.
- Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2014.Google Scholar
- H. Abou-zeid, H. Hassanein, and S. Valentin. Optimal predictive resource allocation: Exploiting mobility patterns and radio maps. In Proc. IEEE GLOBECOM, 2013.Google Scholar
- H. Abou-zeid, H. Hassanein, and S. Valentin. Energy-efficient adaptive video transmission: Exploiting rate predictions in wireless networks. IEEE Transactions on Vehicular Technology, 63(5):2013--2026, June 2014.Google ScholarCross Ref
- M. Ahmed, S. Spagna, F. Huici, and S. Niccolini. A peek into the future: predicting the evolution of popularity in user generated content. In Proc. ACM WSDM, 2013. Google ScholarDigital Library
- A. Ashraf, F. Jokhio, T. Deneke, S. Lafond, I. Porres, and J. Lilius. Stream-based admission control and scheduling for video transcoding in cloud computing. In Proc. IEEE/ACM CCGrid, 2013.Google ScholarDigital Library
- T. Braun, C. Castelluccia, G. Stattenberger, and I. Aad. An analysis of the diffserv approach in mobile environments. In Proc. IQWiM-Workshop, 1999.Google Scholar
- N. Bui, F. Michelinakis, and J. Widmer. A model for throughput prediction for mobile users. In European Wireless, 2014.Google Scholar
- N. Bui, S. Valentin, and J. Widmer. Anticipatory quality-resource allocation for multi-user mobile video streaming. In Proc. IEEE CNTCV, 2015.Google ScholarCross Ref
- N. Bui and J. Widmer. Mobile network resource optimization under imperfect prediction. In Proc. IEEE WoWMoM, 2015.Google ScholarCross Ref
- F. Dobrian, V. Sekar, A. Awan, I. Stoica, D. Joseph, A. Ganjam, J. Zhan, and H. Zhang. Understanding the impact of video quality on user engagement. ACM SIGCOMM Computer Communication Review, 41(4):362--373, 2011. Google ScholarDigital Library
- M. Dräxler and H. Karl. Cross-layer scheduling for multi-quality video streaming in cellular wireless networks. In Proc. IEEE IWCMC, 2013.Google ScholarCross Ref
- J. Froehlich and J. Krumm. Route prediction from trip observations. SAE SP, 2193:53, 2008.Google Scholar
- H.-F. Geerdes, E. Lamers, P. Lourenço, E. Meijerink, U. Türke, S. Verwijmeren, and T. Kürner. Evaluation of reference and public scenarios. Technical Report D5.3, IST-2000-28088 MOMENTUM, 2003.Google Scholar
- Gurobi Optimization, Inc. Gurobi optimizer reference manual, 2015.Google Scholar
- V. Joseph and G. de Veciana. NOVA: QoE-driven optimization of DASH-based video delivery in networks. In Proc. IEEE INFOCOM, 2014.Google ScholarCross Ref
- P. Koutsakis, M. Vafiadis, and H. Papadakis. Prediction-based resource allocation for multimedia traffic over high-speed wireless networks. AEU-International Journal of Electronics and Communications, 2006.Google ScholarCross Ref
- G. Majid, J. Capka, and R. Boutaba. Prediction-based admission control for DiffServ wireless internet. In Proc. IEEE VTC-Fall, 2003.Google Scholar
- R. Margolies, A. Sridharan, V. Aggarwal, R. Jana, N. Shankaranarayanan, V. A. Vaishampayan, and G. Zussman. Exploiting mobility in proportional fair cellular scheduling: Measurements and algorithms. In Proc. IEEE INFOCOM, 2014.Google ScholarCross Ref
- A. K. Moorthy, L. K. Choi, A. C. Bovik, and G. De Veciana. Video quality assessment on mobile devices: Subjective, behavioral and objective studies. IEEE J-STSP, 6(6):652--671, 2012.Google Scholar
- A. J. Nicholson and B. D. Noble. Breadcrumbs: forecasting mobile connectivity. In ACM MobiCom, 2008. Google ScholarDigital Library
- O. Østerbø. Scheduling and capacity estimation in LTE. In Proc. IEEE ITC, 2011. Google ScholarDigital Library
- R. Pantos and W. May. HTTP live streaming. IETF Draft, June, 2010.Google Scholar
- U. Paul, A. P. Subramanian, M. M. Buddhikot, and S. R. Das. Understanding traffic dynamics in cellular data networks. In Proc. IEEE INFOCOM, 2011.Google ScholarCross Ref
- Y. Qiao, J. Skicewicz, and P. Dinda. An empirical study of the multiscale predictability of network traffic. In Proc. IEEE HDPC, 2004. Google ScholarDigital Library
- N. Sadek and A. Khotanzad. Multi-scale high-speed network traffic prediction using k-factor Gegenbauer ARMA model. In IEEE ICC, 2004.Google ScholarCross Ref
- M. Z. Shafiq, L. Ji, A. X. Liu, and J. Wang. Characterizing and modeling internet traffic dynamics of cellular devices. In Proc. ACM SIGMETRICS, 2011. Google ScholarDigital Library
- T. Taleb and A. Ksentini. QoS/QoE predictions-based admission control for femto communications. In Proc. IEEE ICC, 2012.Google ScholarCross Ref
- S. Wang, Y. Xin, S. Chen, W. Zhang, and C. Wang. Enhancing spectral efficiency for LTE-advanced and beyond cellular networks {Guest Editorial}. IEEE Wireless Communications, 21(2):8--9, April 2014.Google ScholarCross Ref
Index Terms
- Anticipatory Admission Control and Resource Allocation for Media Streaming in Mobile Networks
Recommendations
Fair intelligent admission control over resource-feedback DiffServ network
The basic DiffServ model lacks mechanisms to prevent itself from being overloaded and to inform its internal capability to the external world. This paper addresses the problem by presenting a Fair Intelligent Admission Control (FIAC) over an enhanced-...
QoS provisioning for video streaming over SP-driven P2P networks using admission control
CCNC'09: Proceedings of the 6th IEEE Conference on Consumer Communications and Networking ConferenceIn this paper, we present an admission control mechanism for video streaming driven by Service Provider (SP) over P2P networks. SP-driven P2P network is a network in which service provider has a comprehensive control over contracted resources ...
Comments