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On Cooperative Settlement Between Content, Transit and Eyeball ISPs

On Cooperative Settlement Between Content, Transit and Eyeball ISPs. Richard T.B. Ma Columbia University Dah-ming Chiu, John C.S. Lui The Chinese University of Hong Kong Vishal Misra, Dan Rubenstein Columbia University. Outline. Current ISP Settlement Problems ISP Models

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On Cooperative Settlement Between Content, Transit and Eyeball ISPs

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  1. On Cooperative Settlement Between Content, Transit and Eyeball ISPs Richard T.B. Ma Columbia University Dah-ming Chiu, John C.S. Lui The Chinese University of Hong Kong Vishal Misra, Dan Rubenstein Columbia University

  2. Outline • Current ISP Settlement Problems • ISP Models • Profit Sharing Among ISPs • Implications

  3. A view of Internet Service Providers (ISPs) • The Internet is composed of Autonomous Systems (ASes). • An ISP is a business entity. • Might comprise multiple ASes. • Provide Internet access. • Objective: maximizeprofits. ISP

  4. Different classes of ISPs • Eyeball ISPs • Provide Internet access to customers: • Place Large investment in infrastructure. • E.g. AT&T, Verizon … • Content ISPs • Provide contents via the Internet. • Serve customers like: • Transit ISPs • Tier 1 ISPs: global connectivity of the Internet. • Provide transit services for other ISPs. • Cover a large geographic area.

  5. Transit ISP Transit ISP Current ISP settlements Customer-Provider Settlement Zero-Dollar Peering Settlement Transit ISP Eyeball ISP Content ISP

  6. ISP positions on current settlement Transit Eyeball Content Providers

  7. Issues of the current ISP settlements Net Neutrality Debate: Provide Content-based Service Differentiation ? Yes No Eyeball Content Providers Transit Network Balkanization: De-peering between ISPs Transit Transit zero-dollar peering How to appropriately share profits amongst ISPs?

  8. Contribution of this work • Modeling of ISPs • How the revenues are generated • How different kinds of ISPs interact with one another • Profit Sharing Solution Among ISPs • Efficiency • Fairness • Uniqueness • Implications on Bilateral Settlements • Why the current settlements failed • What kind of new settlements should emerge

  9. The Network Model: Eyeball Side r=$ • Geographic Regions (r) • Per Customer Monthly Charge (ar) • Customer Size (Xr) • Eyeball ISP (Bj) • Revenue from a region r (arXr) r=£

  10. Eyeball Side Demand Assumption • Elastic intra-region demand • Customers can switch among ISPs within a region. • New eyeballs may take customers from other eyeballs in the same region. • Customers move to other eyeballs when the original eyeball leaves the system. • Inelastic inter-region demand • Customers cannot switch to ISPs in other regions. • Constant customer size in a region.

  11. The Network Model: Content Side • Content Items (q) • Content ISP (Ci) • Per Customer Revenue for content q (bq) • Content-side Revenue for uploading content q to region r (bqXr) How to share profits amongst ISPs?

  12. How to share profit? -- the baseline case • One content and one eyeball ISP. • One region, US, and one content, ♫. • Egalitarian profit sharing:

  13. How to share profit? -- multiple eyeballs • Symmetry: symmetric eyeball ISPs get the same profit. • Efficiency: summation of all ISPs’ profit equals v. • Fairness: same mutual contribution for any pair of ISPs. Unique solution (Shapley value)

  14. Myerson 1977 Efficiency Symmetry Fairness Shapley 1953 Efficiency Symmetry Dummy Additivity Young 1985 Efficiency Symmetry StrongMonotonicity Shapley 1977 CoNEXT ‘07 Routing Incentive Solution Stability Interconnecting Incentive Properties of Shapley Value The Shapley Value

  15. How to share profit? -- multiple eyeballs n eyeball ISPs. • The unique solution (Shapley value) that satisfies EfficiencySymmetry and Fairness:

  16. Results and implications of profit sharing • The more eyeballs, the more profit the content ISP gets. • Elastic users move between eyeball ISPs. • Multiple eyeball ISPs provide redundancy; • The only content ISP has more leverage. • When one eyeball leaves the system: • The marginal profit loss of the content ISP: • If n=1, the content ISP loses everything if the eyeball leaves. • The content ISP loses only 1/n2 of its original profit.

  17. How to share profit? -- multiple contents m content ISPs. • The unique solution (Shapley value) that satisfies EfficiencySymmetry and Fairness:

  18. Results and implications of profit sharing • The more contents, the more profit the eyeball ISP gets. • Content can be obtained by any content ISP. • Multiple content ISPs provide redundancy; • The only eyeball ISP has more leverage. • The marginal profit loss of the eyeball ISP: • If m=1, the eyeball ISP loses everything if the content leaves. • The eyeball ISP loses only 1/m2 of its original profit.

  19. Profit share -- multiple eyeballs and contents • The unique solution (Shapley value) that satisfies EfficiencySymmetry and Fairness:

  20. Results and implications of ISP profit sharing • Each ISP’s profit is • Inversely proportional to the number of ISPs of its type. • Proportional to the number of ISPs of the opposite type. • Intuition for elastic demand and supply • The more of the same kind provide redundancy. • The less of a kind can obtain more leverage.

  21. Profit share -- eyeballs, transits and contents

  22. Profit share -- eyeballs, transits and contents • Intuition • The more of the same kind provide redundancy. • The less of a kind can obtain more leverage.

  23. Profit share -- multiple regions and items • Revenue sources are separable • Eyeball-side components: • Content-side components:

  24. Profit share -- multiple regions and items • A specific revenue component is shared by • Content ISPs that provide the item • Eyeball ISPs that generate the revenue • Transit ISPs that help the delivery

  25. Profit share – general topologies Dynamic Programming Procedure!

  26. $ $ $ $ $ $ Implications – the value chain $ $ $ $ BR $ $ CR $ $ $ $ $ $

  27. $ $ $ $ $ $ Implications – the value chain $ BR $ $ CR $ $ $ • Revenue Flows • Content-side revenue (CR): Content Transit Eyeball • Eyeball-side revenue (ER): Eyeball Transit Content

  28. $ $ $ $ $ $ Implications – equivalent bilateral settlements Customer Provider Customer $ BR $ $ CR Zero-dollar Peering $ $ $ • When CR ≈ BR, bilateral implementations: • Customer/Provider: Contents & Eyeballs are customers. • Zero-dollar Peering: Transit ISPs peer with each other. • Stable structure for homogenous local ISPs 10 years ago.

  29. $ $ $ $ $ $ Implications – equivalent bilateral settlements $ $ $ CR $ $ $ $ $ $ BR $ $ $ $ $ $ Customer Provider Paid Peering $ $ $ • If CR >> BR, bilateral implementations: • Reverse Customer/Provider: Transits compensate Eyeballs. • Paid Peering: content-side compensate eyeball-side. • New settlements are needed to sustain a stable structure.

  30. Summary • Content-Transit-Eyeball ISP model • Customer demand, revenue generation. • Closed-form Shapley value for regular topologies. • Dynamic Programming for general topologies. • Implications for current bilateral settlements • Transit ISPs might need to compensate Eyeball ISPs, which creates a Reverse Customer/Provider settlement. • Paid Peering settlement might exist among Transit ISPs. • Guideline for • Government: make regulatory policy for the industry. • ISPs: negotiate stable and incentive settlements.

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