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A Shapley Value Perspective on Internet Economics Paris Networking Workshop 2009 Vishal Misra Department of Computer Science Columbia University Joint work with Richard TB Ma, Dah-Ming Chiu, John Lui and Dan Rubenstein

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Outline Network economics research and problems Our research: two problems –Design Efficient and Fair Profit Sharing Mechanisms efficient/optimal –Encourage ISPs to operate at efficient/optimal points

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The Internet is operated by hundreds of interconnected Internet Service Providers (ISPs). An ISP is a autonomous business entity –Provide Internet services. –Common objective: to make profit. Building blocks of the Internet: ISPs

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Three types of ISPs Eyeball ISPs: –Provide Internet access to individual users. –E.g. TimeWarner, Free Content ISPs: –Provide contents on the Internet. Transit ISPs: –Tier 1 ISPs: global connectivity of the Internet. –Provide transit services for other ISPs.

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A motivating example Win-win under Client-Server: –Content providers find customers –Users get information –ISPs obtain revenue Volume-based charge Fixed-rate charge

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What happens with P2P traffic? Win-lose under P2P paradigm: –Content providers pay less –Customers get faster downloads –Content ISP obtains less revenue –Eyeball ISPs handle more traffic In reality: P2P is a nightmare for ISPs.

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Engineering solutions and … beyond Proposed engineering approaches: –ISPs: Drop P2P packets based on port number –Users: Dynamic port selection –ISPs: Deep packet inspection –Users: Disguise by encryption –ISPs: Behavioral analysis A new/global angle: Network EconomicsA new/global angle: Network Economics –Goal: a win-win/fair solution for all. –Related Issues: What is a win-win/fair solution? How do we find it? How do we design algorithms/protocols to achieve?

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Two important issues of the Internet 1. Network Neutrality Debate: Content-based Service Differentiation ? YesNo 2. Network Balkanization: Break-up of connected ISPs 15% of Internet unreachable Level 3Cogent Legal/regulatory policy for the Internet industry: Allow or Not? Not a technical/operation problem, but an economic issue of ISPs. Allow: ISPs might dominate; Not allow: ISPs might die. Either way, suppress the development of the Internet. Threatens the global connectivity of the Internet.

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Other important problems that can be looked at A new/global angle: Network EconomicsA new/global angle: Network Economics –Goal: a win-win/fair solution –Issues: how do we design algorithms/protocols to achieve it?

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Problems we try to solve win-win/fairProblem 1: Find a win-win/fair profit-sharing solution for ISPs. Challenges –Whats the solution? ISPs dont know, even with best intentions. –How do we find it? Complex ISPs structure, computationally expensive. –How do we implement it? Need to be implementable for ISPs.

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One content and one eyeball ISP Profit V = total revenue = content-side + eyeball-side Win-win/fair profit sharing: How to share profit? -- the baseline case

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How to share profit? – two symmetric eyeball ISPs Symmetry: same profit for symmetric eyeball ISPs Efficiency: summation of individual ISP profits equals v Fairness: same mutual contribution for any pair of ISPs Unique solution (Shapley value) Win-win/fair properties:

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History and properties of the Shapley value Shapley Value EfficiencySymmetryFairness Myerson 1977 EfficiencySymmetryDummyAdditivity Shapley 1953 EfficiencySymmetryStrong Monotonicity Young 1985 What is the Shapley value? – A measure of ones contribution to different coalitions that it participates in.

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How do we share profit? -- n symmetric eyeball ISPs Theorem: the Shapley profit sharing solution is

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Results and implications of profit sharing More eyeball ISPs, the content ISP gets larger profit share. –Users may choose different eyeball ISPs; however, must go through content ISP, –Multiple eyeball ISPs provide redundancy –The single content ISP has leverage. Contents profit with one less eyeball: The marginal profit loss of the content ISP: If an eyeball ISP leaves –The content ISP will lose 1/n 2 of its profit. –If n=1, the content ISP will lose all its profit.

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Profit share -- multiple eyeball and content ISPs Theorem: the Shapley profit sharing solution is

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Results and implications of ISP profit sharing Intuition –The larger group of ISPs provides redundancy. –The smaller group of ISPs has leverage. Each ISPs profit share is –Inversely proportional to the number of ISPs of its own type. –Proportional to the number of ISPs of the opposite type.

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Profit share -- eyeball, transit and content ISPs Intuition –The larger group of ISPs provides redundancy. –The smaller group of ISPs has leverage. Theorem: the Shapley profit sharing solution is

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Profit share – general topologies 1. Shapley values under sub-topologies: 2. Whether the profit can still be generated: Theorem: Dynamic Programming

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Current ISP Business Practices: A Macroscopic View Zero-Dollar Peering Customer-Provider Settlement Two forms of bilateral settlements: Provider ISPs Customer ISPs $$$

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Achieving the win-win/fair profit share $$$ $$ $ $ $ $ $$$ $ $ $ $ $ $ Content-side Revenue Eyeball-side Revenue

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Achieving the win-win/fair profit share Two revenue flows to achieve the Shapley profit share: –Content-side revenue: Content Transit Eyeball –Eyeball-side revenue: Eyeball Transit Content $$$ $$ $ $$$ $$ $ Content-side Revenue Eyeball-side Revenue

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Achieving Shapley solution by bilateral settlements $$$ $$ $ $$$ $$ $ When CR BR, bilateral implementations: –Customer-Provider settlements (Transit ISPs as providers) –Zero-dollar Peering settlements (between Transit ISPs) –Current settlements can achieve fair profit-share for ISPs. Providers Customers Zero-dollar Peering Content-side Revenue Eyeball-side Revenue

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Achieving Shapley solution by bilateral settlements $$$ $$ $ $$$ $$ $ $$$ $$ $ $$$ $$ $ If CR >> BR, bilateral implementations: –Reverse Customer-Provider –Reverse Customer-Provider (Transits compensate Eyeballs) –Paid Peering –Paid Peering (Content-side compensates eyeball-side) –New settlements are needed to achieve fair profit-share. CustomerProvider Paid Peering Eyeball-side Revenue Content-side Revenue

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Recap: ISP Practices from a Macroscopic View Zero-Dollar Peering Customer-Provider Settlement Two current forms of bilateral settlements: Reverse Customer- Provider Settlement Paid Peering Our Implication: Two new forms of bilateral settlements: Next, a Microscopic View to inspect on ISP behaviors $$$

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Problems we try to solve win-win/fairProblem 1: Find a win-win/fair profit-sharing solution for ISPs. Challenges –Whats the solution? ISPs dont know, even with best intentions. –Answer: The Shapley value. –How do we find it? Complex ISPs structure, computationally expensive. –Result: Closed-form solution and Dynamic Programming. –How do we implement it? Need to be implementable for ISPs. –Implication: New bilateral settlements.

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Problems we try to solve win-win/fairProblem 1: Find a win-win/fair profit-sharing solution for ISPs. Challenges –Whats the solution? ISPs dont know, even with best intentions. –Answer: The Shapley value. –How do we find it? Complex ISPs structure, computationally expensive. –Result: Closed-form solution and Dynamic Programming. –How do we implement? Need to be implementable for ISPs. –Implication: New bilateral settlements. efficient/optimalProblem 2: Encourage ISPs to operate at efficient/optimal points. Challenges –How do we induce good behavior? Selfish behavior may hurt other ISPs. –What is the impact on the entire network? Equilibrium is efficient?

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Current ISP Business Practices: A Micro Perspective Three levels of ISP decisions Interconnecting decision E Routing decisions R (via BGP) Bilateral settlements Shortest Path Routing Hot-potato Routing Source Destination Zero-Dollar Peering Customer-Provider Settlements Provider ISP Customer ISP Settlement affects E, R provider charges high Interconnection withdrawal Route change

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Peering links at both coasts Locally connect to both backbone ISPs RouteTopology An ideal case of the ISP decisions Two backbone ISPs Two local ISPs End-to-end service generates revenue Routing costs on links Backbone ISP 1 Backbone ISP 2 Local ISP 1 Local ISP 2 Fixed Revenue A simple example: Well-connected topology W = 1

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Routing cost model x 2 /4 Assumptions (based on current practices) –Routing costs on links, e.g. bandwidth capacity and maintenance. –Going across the country is more expensive. –More expensive when link is more congested. Costs increase with link loads –Standard queueing theory results. –Capital investment for upgrades.

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x 2 2 /4 x 7 2 /4 x 4 2 /8 x 5 2 /8 x 1 2 /16 x 6 2 /16 x 3 2 /16 x 8 2 /16 1/2 RouteTopology Global Min Cost An ideal case of the ISP decisions Two backbone ISPs Two local ISPs End-to-end service generates revenue Routing costs on links Backbone ISP 1 Backbone ISP 2 Local ISP 1 Local ISP 2 Fixed RevenueCost | Profit A simple example: Well-connected topology W = 1 We normalize the total required traffic load to be 1. MIN routing cost and MAX profit

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x 2 2 /4 x 7 2 /4 x 4 2 /8 x 5 2 /8 x 1 2 /16 x 6 2 /16 x 3 2 /16 x 8 2 /16 1/2 RouteTopology Global Min Cost Problems with the current practice Cost | Profit Behavior 1: ISPs interconnect selfishly to maximize profits! e.g. Backbone ISPs charge local ISPs. Two backbone ISPs Two local ISPs End-to-end service generates revenue Routing costs on links A simple example: MIN routing cost and MAX profit Increased routing and reduced profit Well-connected topology Topology Balkanization

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x 2 2 /4 x 7 2 /4 x 4 2 /8 x 5 2 /8 x 1 2 /16 x 8 2 /16 1/2 RouteTopology Global Min Cost Cost | Profit Hot Potato 1 Problems with the current practice Behavior 2: ISPs route selfishly to maximize profits! e.g. upper backbone ISP wants to use hot-potato routing to reduce its routing cost. Profit reduction by routing inefficiency Behavior 1: ISPs interconnect selfishly to maximize profits! Topology Balkanization Increased routing and reduced profit Two backbone ISPs Two local ISPs End-to-end service generates revenue Routing costs on links A simple example:

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Issues of Current ISP Settlement: A Micro Perspective Global Ideal case: cooperative ISPs RouteTopologyCost | Profit ( maximized )Connectivity Global Min Cost Well- connected RouteTopologyCost | Profit ( reduced )Connectivity Global Min Cost Balkanized RouteTopologyCost | Profit ( further reduced )Connectivity Hot Potato Balkanized ISPs selfishly route traffic ISPs selfishly interconnect How to encourage ISPs to operate at efficient/optimal points?

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collects revenue from customers distributes profits to ISPs Our solution: The Shapley Mechanism Recall: three levels of ISP decisions Interconnecting decision E Routing decisions R Bilateral settlements Source Destination Zero-Dollar Peering Customer-Provider Settlements Provider ISP Customer ISP Settlement affects E, R Multilateral settlements (E,R) $$$ $$

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Local decisions: E i,R i EiEi RiRi Given: Objective: to maximize i (E,R) Our solution: The Shapley Mechanism Each ISPs local interconnecting and routing decisions.

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x 2 2 /4 x 7 2 /4 x 4 2 /8 x 5 2 /8 x 1 2 /16 x 8 2 /16 RouteTopology Results: Routing Incentive Cost | Profit Local Min Cost 1 Hot Potato 1/4 3/4 1/2 Global Min Cost Recall the inefficiency situation Shapley mechanism distributes profit ISPs route selfishly to maximize profits! E.g. the upper ISP wants to minimize local routing cost Best strategy for all ISPs: global min cost routing Profit increaseProfit maximized

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Given any fixed interconnecting topology E, ISPs can locally decide routing strategies {R i * } to maximize their profits. Theorem (Incentive for routing): Any ISP i can maximize its profit i by locally minimizing the global routing cost. –Implication: ISPs adapt to global min cost routes. Corollary (Nash Equilibrium): Any global min cost routing decision is a Nash equilibrium for the set of all ISPs. –Implication: global min cost routes are stable. Results: Incentives for using Optimal Routes Surprising! Local selfish behaviors coincide with global optimal solution!

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x 2 2 /4 x 7 2 /4 x 4 2 /8 x 5 2 /8 x 1 2 /16 x 8 2 /16 RouteTopology Results: Interconnecting Incentive Cost | Profit 1/2 Global Min Cost x 6 2 /16 7/12 5/12 x 3 2 /16 ISPs interconnect selfishly to maximize profits! Recall: the best strategy for all ISPs is to use global min cost routes. E.g. the left local ISP connects to the low backbone ISP. Profit increase Further the right local ISP connects to the upper backbone ISP.

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For any topology, a global optimal route R * is used by all ISPs. ISPs can locally decide interconnecting strategies {E i * } to maximize their profits. Theorem (Incentive for interconnecting): By interconnecting, ISPs will have non-decreasing profits. –Implication: ISPs have incentive to interconnect. –Does not mean: All pairs of ISPs should be connected. Redundant links might not reduce routing costs. Sunk cost is not considered. Results: Incentive for Interconnecting

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Micro perspective ISP settlement: result summary Selfishly interconnect and route RouteTopologyCost | ProfitConnectivity Global Min Cost well- connected RouteTopologyCost | ProfitConnectivity Global Min Cost Balkanized RouteTopologyCost | ProfitConnectivity Hot Potato Balkanized ISPs have incentive to interconnect ISPs have incentive to use optimal routes solves the selfish interconnecting problem solves the selfish routing problem

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Problems we try to solve win-win/fairProblem 1: Find a win-win/fair profit-sharing solution for ISPs. Challenges –Whats the solution? ISPs dont know, even with best intentions. –Answer: The Shapley value –How to find it? Complex ISPs structure, computationally expensive. –Result: Closed-form sol. and Dynamic Programming –How to implement? Need to be implementable for ISPs. –Implication: New bilateral settlements efficient/optimalProblem 2: Encourage ISPs to operate at efficient/optimal points. Challenges –How to induce good behavior? Selfish behavior may hurt other ISPs. –Answer: The Shapley mechanism –Result: Incentives for optimal routes and interconnection –What is the impact of the entire network? Equilibrium is efficient? –Result: Optimal global Nash equilibrium

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Guideline for –ISPs: negotiate stable and incentive settlements. –Governments: make regulatory policy for the industry. New Application and Properties of the Shapley Value Shapley Value: Contributions to Coalitions EfficiencySymmetryFairness Myerson 1977 EfficiencySymmetryDummyAdditivity Shapley 1953 EfficiencySymmetryStrong Monotonicity Young 1985 ISP Routing Incentive ISP Interconnecting Incentive Ma et al. 2007 ISP Profit Sharing Ma et al. 2008

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Related Publications Richard T.B. Ma, Dahming Chiu, John C.S. Lui, Vishal Misra and Dan Rubenstein, On Cooperative Settlement Between Content, Transit and Eyeball Internet Service Providers, Proceedings of 2008 ACM Conference on Emerging network experiment and technology (CoNEXT 2008), Madrid, Spain, December, 2008 Richard T.B. Ma, Dahming Chiu, John C.S. Lui, Vishal Misra and Dan Rubenstein, The Shapley Value: Its Use and Implications on Internet Economics, Allerton Conference on Communication, Control and Computing, September, 2008 Richard T.B. Ma, Dah-ming Chiu, John C.S. Lui, Vishal Misra and Dan Rubenstein, Interconnecting Eyeballs to Content: A Shapley Value Perspective on ISP Peering and Settlement, ACM NetEcon, Seattle, WA, August, 2008 Richard T.B. Ma, Dahming Chiu, John C.S. Lui, Vishal Misra and Dan Rubenstein, Internet Economics: The use of Shapley value for ISP settlement, Proceedings of 2007 ACM Conference on Emerging network experiment and technology (CoNEXT 2007), Columbia University, New York, December, 2007

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( )=2.4/6=0.4 Empty S (S(, )) v( )=0 v( )=0.2v( )- v( )=0.8 v( )=0 v( )- v( )=0.8 v( )=0.6v( )- N: total # of ISPs, e.g. N=3 : set of N! orderings S(,i): set of ISPs in front of ISP i The Shapley value mechanism

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