Cooperative content distribution and traffic engineering in an ISP network

Traditionally, Internet Service Providers (ISPs) make profit by providing Internet connectivity, while content providers (CPs) play the more lucrative role of delivering content to users. As network connectivity is increasingly a commodity, ISPs have a strong incentive to offer content to their subscribers by deploying their own content distribution infrastructure. Providing content services in an ISP network presents new opportunities for coordination between traffic engineering (to select efficient routes for the traffic) and server selection (to match servers with subscribers). In this work, we develop a mathematical framework that considers three models with an increasing amount of cooperation between the ISP and the CP. We show that separating server selection and traffic engineering leads to sub-optimal equilibria, even when the CP is given accurate and timely information about the ISP's network in a partial cooperation. More surprisingly, extra visibility may result in a less efficient outcome and such performance degradation can be unbounded. Leveraging ideas from cooperative game theory, we propose an architecture based on the concept of Nash bargaining solution. Simulations on realistic backbone topologies are performed to quantify the performance differences among the three models. Our results apply both when a network provider attempts to provide content, and when separate ISP and CP entities wish to cooperate. This study is a step toward a systematic understanding of the interactions between those who provide and operate networks and those who generate and distribute content.

[1]  Ratul Mahajan,et al.  Measuring ISP topologies with Rocketfuel , 2004, IEEE/ACM Transactions on Networking.

[2]  Michael L. Littman,et al.  A Distributed Reinforcement Learning Scheme for Network Routing , 1993 .

[3]  Aditya Akella,et al.  Cooperative Interdomain Traffic Engineering Using Nash Bargaining and Decomposition , 2007, IEEE/ACM Transactions on Networking.

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

[5]  Sam C. M. Lee,et al.  Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization , 2008, IEEE Transactions on Parallel and Distributed Systems.

[6]  Mikkel Thorup,et al.  Internet traffic engineering by optimizing OSPF weights , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[7]  Abraham Silberschatz,et al.  P4p: provider portal for applications , 2008, SIGCOMM '08.

[8]  Christian Scheideler,et al.  Can ISPS and P2P users cooperate for improved performance? , 2007, CCRV.

[9]  A. Rubinstein,et al.  The Nash bargaining solution in economic modelling , 1985 .

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

[11]  Daniel Pérez Palomar,et al.  A tutorial on decomposition methods for network utility maximization , 2006, IEEE Journal on Selected Areas in Communications.

[12]  Daniel O. Awduche,et al.  Requirements for Traffic Engineering Over MPLS , 1999, RFC.

[13]  John C. S. Lui,et al.  On the interaction of multiple overlay routing , 2005, Perform. Evaluation.

[14]  J. Wardrop ROAD PAPER. SOME THEORETICAL ASPECTS OF ROAD TRAFFIC RESEARCH. , 1952 .

[15]  Tim Roughgarden,et al.  How bad is selfish routing? , 2000, Proceedings 41st Annual Symposium on Foundations of Computer Science.

[16]  Vishal Misra,et al.  On Cooperative Settlement Between Content, Transit, and Eyeball Internet Service Providers , 2008, IEEE/ACM Transactions on Networking.

[17]  Fabián E. Bustamante,et al.  Taming the torrent: a practical approach to reducing cross-isp traffic in peer-to-peer systems , 2008, SIGCOMM '08.

[18]  Mikkel Thorup,et al.  Performance of estimated traffic matrices in traffic engineering , 2003, SIGMETRICS '03.

[19]  J. G. Wardrop,et al.  Some Theoretical Aspects of Road Traffic Research , 1952 .

[20]  Mung Chiang,et al.  Cooperative content distribution and traffic engineering , 2008, NetEcon '08.

[21]  J. Nash THE BARGAINING PROBLEM , 1950, Classics in Game Theory.

[22]  Donald F. Towsley,et al.  On the interaction between overlay routing and underlay routing , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[23]  Ariel Rubinstein,et al.  A Course in Game Theory , 1995 .

[24]  Yin Zhang,et al.  On selfish routing in Internet-like environments , 2003, IEEE/ACM Transactions on Networking.

[25]  Mung Chiang,et al.  Link-State Routing With Hop-by-Hop Forwarding Can Achieve Optimal Traffic Engineering , 2011, IEEE/ACM Trans. Netw..

[26]  Aditya Akella,et al.  Cooperative Inter-Domain Traffic Engineering Using Nash Bargaining and Decomposition , 2007 .

[27]  Michael J. Freedman,et al.  Prices are right: managing resources and incentives in peer-assisted content distribution , 2008, IPTPS.

[28]  A. Rubinstein,et al.  A Course in Game Theory , 1995 .

[29]  Mung Chiang,et al.  Link-State Routing with Hop-by-Hop Forwarding Can Achieve Optimal Traffic Engineering , 2008, INFOCOM.

[30]  Dimitri P. Bertsekas,et al.  Nonlinear Programming , 1997 .

[31]  Ying Li,et al.  DaVinci: dynamically adaptive virtual networks for a customized internet , 2008, CoNEXT '08.