Joint request routing and video adaptation in collaborative VoD systems

Collaborative content storing and requesting are emerging solutions to Video-on-Demand (VoD) systems challenged by the explosive growth of online video demand. By exploiting the collaboration among the serving nodes in a VoD system, the new solutions dramatically increase the system capacity. In this work, we focus on the in-system collaborative request routing problem. Together with the video-adaptation techniques, we optimize the aggregate utility of end users while keeping the maximum link congestion under a given upper bound. We prove that the formulated problem is NP-hard, and solve it in two phases: a rate-selection phase and a fixed-rate routing phase. Afterwards, we convert the raw output of the proposed algorithm to a hop-by-hop routing-decision protocol which can be easily implemented in most existing routers. Numerical results show that our solution to the fixed-rate routing problem supports up to 60% more traffic than existing shortest-path algorithm. With joint video adaptation, our algorithm for optimizing utility outperforms the simple greedy method up to 18%.

[1]  Aleksandar Kuzmanovic,et al.  Drafting behind Akamai (travelocity-based detouring) , 2006, SIGCOMM '06.

[2]  William R. McShane,et al.  A review of pedestrian safety models for urban areas in Low and Middle Income Countries , 2016 .

[3]  Ramesh Johari,et al.  Traffic Engineering vs. Content Distribution: A Game Theoretic Perspective , 2009, IEEE INFOCOM 2009.

[4]  Jochen Könemann,et al.  Faster and Simpler Algorithms for Multicommodity Flow and Other Fractional Packing Problems , 2007, SIAM J. Comput..

[5]  Sem C. Borst,et al.  Distributed Caching Algorithms for Content Distribution Networks , 2010, 2010 Proceedings IEEE INFOCOM.

[6]  Baohua Zhao,et al.  A fast, simple and near-optimal content placement scheme for a large-scale VoD system , 2012, 2012 IEEE International Conference on Communication Systems (ICCS).

[7]  Lisa Fleischer,et al.  Approximating Fractional Multicommodity Flow Independent of the Number of Commodities , 2000, SIAM J. Discret. Math..

[8]  Van Jacobson,et al.  Adaptive web caching: towards a new global caching architecture , 1998, Comput. Networks.

[9]  Vyas Sekar,et al.  Understanding the impact of video quality on user engagement , 2011, SIGCOMM.

[10]  Supratim Deb,et al.  Real-Time Video Multicast in WiMAX Networks , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[11]  Shih-Fu Chang,et al.  Video Adaptation: Concepts, Technologies, and Open Issues , 2005, Proceedings of the IEEE.

[12]  Vijay Arya,et al.  On Managing Quality of Experience of Multiple Video Streams in Wireless Networks , 2012, IEEE Transactions on Mobile Computing.

[13]  George Karakostas,et al.  Faster approximation schemes for fractional multicommodity flow problems , 2008, TALG.

[14]  Mung Chiang,et al.  Cooperative content distribution and traffic engineering in an ISP network , 2009, SIGMETRICS '09.

[15]  Nick McKeown,et al.  OpenFlow: enabling innovation in campus networks , 2008, CCRV.

[16]  Guangyu Shi,et al.  TECC: Towards collaborative in-network caching guided by traffic engineering , 2012, 2012 Proceedings IEEE INFOCOM.

[17]  Jochen Könemann,et al.  Faster and simpler algorithms for multicommodity flow and other fractional packing problems , 1998, Proceedings 39th Annual Symposium on Foundations of Computer Science (Cat. No.98CB36280).

[18]  H. Edwin Romeijn,et al.  A class of greedy algorithms for the generalized assignment problem , 2000, Discret. Appl. Math..