On the interaction between content-oriented traffic scheduling and revenue sharing among providers

The Internet consists of economically selfish players in terms of access/transit connection, content distribution, and users. Such selfish behaviors often lead to techno-economic inefficiencies such as unstable peering and revenue imbalance. Recent research results suggest that cooperation in revenue sharing (thus multi-level ISP settlements) can be a candidate solution for the problem of unfair revenue share. However, it is unclear whether providers are willing to behave cooperatively. In this paper, we study the interaction between how content-oriented traffic scheduling at the edge is and how stable the intended cooperation is. We consider three traffic scheduling policies having various degrees of content-value preference, compare them in terms of implementation complexity, network neutrality, and stability of cooperation, and present interesting trade-offs among them.

[1]  A. Robert Calderbank,et al.  Pricing under Constraints in Access Networks: Revenue Maximization and Congestion Management , 2010, 2010 Proceedings IEEE INFOCOM.

[2]  R. J. Aumann,et al.  Cooperative games with coalition structures , 1974 .

[3]  Jean C. Walrand,et al.  Pricing and revenue sharing strategies for Internet service providers , 2005, IEEE Journal on Selected Areas in Communications.

[4]  Yung Yi,et al.  On the interaction between ISP revenue sharing and network neutrality , 2010, CoNEXT '10 Student Workshop.

[5]  D. Clark,et al.  Complexity of Internet Interconnections: Technology, Incentives and Implications for Policy , 2007 .

[6]  S. Hart,et al.  On the endogenous formation of coalitions , 1983 .

[7]  Vishal Misra,et al.  On cooperative settlement between content, transit, and eyeball internet service providers , 2011, TNET.

[8]  Amogh Dhamdhere,et al.  The Internet is flat: modeling the transition from a transit hierarchy to a peering mesh , 2010, CoNEXT.

[9]  Yung Yi,et al.  On the Shapley-Like Payoff Mechanisms in Peer-Assisted Services with Multiple Content Providers , 2010, GAMENETS.

[10]  Vishal Misra,et al.  Internet Economics: The Use of Shapley Value for ISP Settlement , 2007, IEEE/ACM Transactions on Networking.

[11]  P. P. Shenoy,et al.  On coalition formation: a game-theoretical approach , 1979 .

[12]  Andrew Odlyzko The Volume and Value of Information , 2012 .

[13]  L. S. Shapley,et al.  17. A Value for n-Person Games , 1953 .

[14]  John Musacchio,et al.  A Two-Sided Market Analysis of Provider Investment Incentives with an Application to the Net-Neutrality Issue , 2009 .

[15]  Z. Abbassi,et al.  Multi-level Revenue Sharing for Viral Marketing , 2011 .

[16]  Serge Fdida,et al.  Federation of virtualized infrastructures: sharing the value of diversity , 2010, CoNEXT.

[17]  Yung Yi,et al.  On the stability of ISPs' coalition structure: Shapley value based revenue sharing , 2012, 2012 46th Annual Conference on Information Sciences and Systems (CISS).

[18]  Andreas Tutic The Aumann-DrèZE Value, the Wiese Value, and stability: a Note , 2010, IGTR.

[19]  A. Odlyzko Network Neutrality, Search Neutrality, and the Never-ending Conflict between Efficiency and Fairness in Markets , 2008 .