Network Economics and ISP Settlement Problems Tianbai Ma Department of Electrical Engineering...

Network Economics and ISP Settlement Problems

Tianbai Ma

Department of Electrical Engineering

Columbia University

Outline

• Network economics research and problems

• Current research: two problems

• My research – past and future

ISP ISPISP

• 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

ISP ISPISP

Three types of ISPs

• Eyeball ISPs:

– Provide Internet access to individual users.– E.g. PCCW

• Content ISPs:

– Provide contents on the Internet.• Transit ISPs:

– Tier 1 ISPs: global connectivity of the Internet.– Provide transit services for other ISPs.

BC T

An motivating example

ISPB

$5/Gb

ISPB

$50/month

$50/month

ISPB

$50/month

ISPC

• Win-win:– Content provider finds customers

– Customers get content

– ISPs obtain revenue

Volume-based charge

Fixed charge

ISPC

What happens with P2P traffic?

$5/Gb

ISPB

$50/month

$50/month

ISPB

$50/month

• Win-lose under P2P paradigm:– Content provider pays less

– Customers get faster download

– Content ISP obtains less revenue

– Eyeball ISPs handle more traffic

• Consequence:– ISPs want to avoid P2P traffic

ISPB

Engineering solutions and … beyond

• Consequence:– ISPs want to avoid P2P traffic

• Proposed engineering solutions:– Strategy of ISPs: Limit P2P traffic rate

– Counter-strategy of users: Encryption

– Counter-strategy of ISPs: Deep packet inspection

• A new/global angle: Network EconomicsA new/global angle: Network Economics– Goal: a win-win/fair solution

– Issue: how to design algorithms/protocols to achieve?

– An exciting and upcoming area:• Inter-disciplinary ： CS, Economics, Operation Research, Policy …• Stanford, CMU, UC Santa Cruz and etc. build new courses/department.

Other important problems that can be looked at

ISPB

ISPC

ISPT

ISPT

1. Network Neutrality Debate: Content-based Service Differentiation ?

Yes No

2. Network Balkanization: Break-ups of Connected ISPs

15% of Internet unreachableLevel 3 Cogent

Legal/regulatory policy for the Internet industry.

Not only a technical/operation problem, but also economic issues.

Some ISPs dominate or ISPs cannot survive.

Suppress the development of the Internet.

Threatens the global connectivity of the Internet.

Other important problems that can be looked at

ISPB

ISPC

ISPT

ISPT

• A new/global angle: Network EconomicsA new/global angle: Network Economics– Goal: a win-win/fair solution

– Issues: how to design algorithms/protocols to achieve?

Problems we try to solve

• Problem 1: Find a win-win/fairwin-win/fair profit-sharing solution for ISPs.• Challenges

– What’s the solution? ISPs don’t know, even with best intentions.

– How to find it? Complex ISPs structure, computationally expensive.

– How to implement? Need to be implementable for ISPs.

• One content and one eyeball ISP

• Profit V = total revenue = content-side + eyeball-side

• Win-win/fair profit sharing:

C1 B1

How to share profit? -- the baseline case

j = j = V21

B1 C1

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

j = j = jB1 B2 B

j + 2j = VC1 B

Unique solution (Shapley value)

j = VC1 3

2

61j = VB

Win-win/fair properties:

B1j - V = j - 0

C1 21

C1

B2

B1

History and properties of the Shapley value

Shapley Value

Efficiency Symmetry Fairness

Myerson 1977

Efficiency Symmetry Dummy Additivity

Shapley 1953

Efficiency Symmetry Strong Monotonicity

Young 1985

What is the Shapley value? – A measure of one’s contribution to different coalitions that it participates in.

How to share profit? -- n symmetric eyeball ISPs

• Theorem: the Shapley profit sharing solution is

j = V, j = Vn+1n

n(n+1)1

B C

C1

B2

B1

Bn

Results and implications of profit sharing

C1

B1

Bn-1

• More eyeball ISPs, the content ISP gets larger profit share.– Users may choose different eyeball ISPs; ho

wever, must go through content ISP,

– Multiple eyeball ISPs provide redundancy ， – The single content ISP has leverage.

• Content’s profit with one less eyeball: • The marginal profit loss of the content ISP:

If an eyeball ISP leaves– The content ISP will lose 1/n2 of its profit.

– If n=1, the content ISP will lose all its profit.

j = V, j = Vn+1n

n(n+1)1

B C

Bn

nn-1j’ = VC

Dj = V - V = - j n+1n

nn-1 1

n2C C

Profit share -- multiple eyeball and content ISPs

C2

C1

Cm

B1

B2

Bn


j = V, j = Vn(n+m)m

m(n+m)n

CB

Results and implications of ISP profit sharing

• Intuition– The larger group of ISPs provides redundancy.

– The smaller group of ISPs has leverage.

C2

C1

Cm

B1

B2

Bn

• Each ISP’s profit share is– Inversely proportional to the

number of ISPs of its own type.

– Proportional to the number of ISPs of the opposite type.

j = , j = nm

(n+m)V n

m(n+m)V

B C

Sm=1

m

Sk=1

k

n+m+kV ( )m

m ( )kk ( )n+m+k-1

m+kj =

Sn=1

n

Sk=1

k

n+m+kV ( )n

n ( )kk ( )n+m+k-1

n+kj =

Sm=1

m

Sn=1

n

n+m+kV ( )m

m ( )nn ( )n+m+k-1

m+nj =

B

C

T

C2

C1

Cm

B1

B2

Bn

T2

T1

Tk

Profit share -- eyeball, transit and content ISPs

• Intuition– The larger group of ISPs provides redundancy.

– The smaller group of ISPs has leverage.


Profit share – general topologies

B2

B1

C1 T1

jC1 = [0 + V + V + V] = V41

31

31

125

ji = [S ji(N \{j}) + V{i is veto}]j≠iN

1

jC1 = 0

B2

B1

C1 T1

jC1 = 1/3V

B2

B1

C1 T1

jC1 = 1/3V

B2

B1

C1 T1

1. Shapley values under sub-topologies:

C1 is veto.

B2

B1

C1 T1

2. Whether the profit can still be generated:

Theorem: Dynamic Programming ！

ISP business practices: a macro perspective

2. Zero-Dollar Peering

1. Customer-Provider Settlement

Two forms of bilateral settlements:Two forms of bilateral settlements:

ISPT

ISPT

ISPB

ISPC

Provider ISPs

Customer ISPs

$$$$$$

T1

T2

T3

T4

C2

C1

C3

B2

B3

B1

B2

Eyeball ISPsContent

ISPsTransit ISPs

Implications – the value chain

$ $$

$ $

$ $

$$

$ $$

$

$

$$ $$

Content-side Content-side RevenueRevenue

Eyeball-side Eyeball-side RevenueRevenue

T1

T2

T3

T4

C2

C1

C3

B2

B3

B1

B2

Eyeball ISPsContent

ISPsTransit ISPs

Implications – the value chain

• Shapley value suggested revenue flows:– Content-side revenue: Content Transit Eyeball

– Eyeball-side revenue: Eyeball Transit Content

$ $$

$ $$

$ $$

$$$



T1

T2

T3

T4

C2

C1

C3

B2

B3

B1

B2

Eyeball ISPsContent

ISPsTransit ISPs

Implications – equivalent bilateral settlements

$ $$

$ $$

$ $$

$$$

• When CR ≈ BR, bilateral implementations:– Customer-Provider settlements (Transit ISPs as providers)– Zero-dollar Peering settlements (between Transit ISPs)– Stable structure when local ISPs are homogeneous.

Providers

CustomersCustomers

Zero-dollarPeering



T1

T2

T3

T4

C2

C1

C3

B2

B3

B1

B2

Eyeball ISPsContent

ISPsTransit ISPs

Implications – equivalent bilateral settlements

$ $$

$ $ $

$ $$

$$$

$ $$

$ $ $$ $$

$ $ $

• If CR >> BR, bilateral implementations:– Reverse Customer-ProviderReverse Customer-Provider (Transits compensate Eyeballs)– Paid PeeringPaid Peering (Content-side compensates eyeball-side)– New settlements will emerge to maintain a stable structure.

Customer Provider

Paid Peering






– Answer: The Shapley value.


– Result: Closed-form solution and Dynamic Programming.


– Implication: New bilateral settlements.

Recap: ISP practices from a macro perspective

2. Zero-Dollar Peering

1. Customer-Provider Settlement

Two current forms of bilateral Two current forms of bilateral settlements:settlements:

ISPT

ISPT

ISPB

ISPC

3. Inverse Customer-Provider Settlement

4. Paid Peering

Two new forms of bilateral settlements:Two new forms of bilateral settlements:




– Answer: The Shapley value.


– Result: Closed-form solution and Dynamic Programming.


– Implication: New bilateral settlements.

• Problem 2: Encourage ISPs to operate at efficient/optimalefficient/optimal points.• Challenges

– How to induce good behavior? Selfish behavior may hurt other ISPs.

– What is the impact of the entire network? Equilibrium is efficient?

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-DollarPeering

Customer-Provider Settlements

Provider ISP

Customer ISP Customer ISP

Settlement affects E, R provider charges high

Interconnection withdrawal

Route change

Peering links at

both coasts

Locally connect to

both backbone ISPs

Route TopologyAn 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

Routing cost model

x2/4

• 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.

x22/4

x72/4

x42/8 x5

2/8

x12/16

x62/16

x32/16

x82/16

1/2

1/2

Route Topology

Global Min Cost

An ideal case of the ISP decisions

Two backbone ISPs

Two local ISPs



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

x22/4

x72/4

x42/8 x5

2/8

x12/16

x62/16

x32/16

x82/16

1/2

1/2

Route Topology

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



A simple example:

MIN routing cost and MAX profitIncreased routing and reduced profitWell-connected topologyTopology Balkanization

x22/4

x72/4

x42/8 x5

2/8

x12/16

x82/16

1/2

1/2

Route Topology

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 BalkanizationIncreased routing and reduced profit

Two backbone ISPs

Two local ISPs



A simple example:

Issues of Current ISP Settlement: A Micro Perspective

Global Ideal case: cooperative ISPs

Route Topology Cost | Profit (maximized) Connectivity

Global Min Cost

Well-connected

Route Topology Cost | Profit (reduced) Connectivity

Global Min Cost

Balkanized

Route TopologyCost | Profit (further

reduced)Connectivity

Hot Potato

Balkanized

ISPs selfishly route traffic

ISPs selfishly interconnect

How to encourage ISPs to operate at efficient/optimal points?How to encourage ISPs to operate at efficient/optimal points?

j collects revenue from customers

j distributes profits to ISPs

Our solution: The Shapley Mechanism j

Recall: three levels of ISP decisions• Interconnecting decision E• Routing decisions R• Bilateral settlements

Source

Destination Zero-DollarPeering

Customer-Provider Settlements

Provider ISP

Customer ISP Customer ISP

Settlement affects E, R

Multilateral settlements j

j(E,R)$$$

$$

$$

Local decisions: Ei,Ri

Ei

Ri

Given: j

Objective: to maximize ji(E,R)

Our solution: The Shapley Mechanism jEach ISP’s local interconnecting and routing decisions.

x22/4

x72/4

x42/8 x5

2/8

x12/16

x82/16

Route TopologyResults: Routing Incentive

Cost | Profit

Local Min Cost

1

Hot Potato

j

1/4

3/4

1/2

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

• Given any fixed interconnecting topology E, ISPs can locally decide routing strategies {Ri

*} to maximize their profits.

• Theorem (Incentive for routing): Any ISP i can maximize its profit ji 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!

x22/4

x72/4

x42/8 x5

2/8

x12/16

x82/16

Route TopologyResults: Interconnecting Incentive

Cost | Profit j

1/2

1/2

Global Min Cost

x62/16

7/12

5/12

x32/16

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

Profit increase

Further the right local ISP connects to the

upper backbone ISP.

• For any topology, a global optimal route R* is used by all ISPs. ISPs can locally decide interconnecting strategies {Ei

*} 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

Micro perspective ISP settlement: result summarySelfishly interconnect and route

Route Topology Cost | Profit Connectivity

Global Min Cost

well-connected


Global Min Cost

Balkanized


Hot Potato

Balkanized

ISPs have incentive to interconnect

ISPs have incentive to use optimal routes

j

j

j solves the selfish interconnecting problem

j solves the selfish routing problem




– Answer: The Shapley value


– Result: Closed-form sol. and Dynamic Programming


– Implication: New bilateral settlements



– Answer: The Shapley mechanism

– Result: Incentives for optimal routes and interconnection


– Result: Optimal global Nash equilibrium

• 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

Efficiency Symmetry Fairness

Myerson 1977

Efficiency Symmetry Dummy Additivity

Shapley 1953

Efficiency Symmetry Strong Monotonicity

Young 1985

ISP Routing Incentive

ISP Interconnecting Incentive

Ma et al. 2007

ISP Profit Sharing

Ma et al. 2008

My research: current work

Network

Approaches

Internet

Coalition Game Theory, Mechanism Design

Problem ISP Settlement

Publications

On Cooperative Settlement Between Content, Transit and Eyeball Internet Service Providers.Proceedings of ACM Conference on Emerging network experiment and technology (CoNEXT '08)

The Shapley Value: Its Use and Implications on Internet Economics.Proceedings of Allerton Conference on Communication, Control and Computing, 2008.

Interconnecting Eyeballs to Content: A Shapley Value Perspective on ISP Peering and Settlement.Proceedings of ACM Network Economics (NetEcon '08)

Internet Economics: The use of Shapley value for ISP settlement.Proceedings of ACM Conference on Emerging network experiment and technology (CoNEXT '07)

My research: past work

Non-cooperative Game Theory, Mechanism Design

Network

Approaches

P2PProblem Free-riding and Incentives

Incentive and Service Differentiation in P2P Networks: A Game Theoretic Approach.IEEE/ACM Transactions on Networking, 14(5), October, 2006.

A Game Theoretic Approach to Provide Incentive and Service Differentiation in P2P Networks.Proceedings of ACM Sigmetrics/Performance, June, 2004.

An Incentive Mechanism for P2P Networks.Proceedings of IEEE International Conference on Distributed Computing Systems (ICDCS 04).

Stochastic Analysis, Non-cooperative Game Theory

Network

Approaches

WirelessProblem Selfish Behaviors in MAC Protocols

An Analysis of Generalized Slotted-Aloha Protocols.IEEE/ACM Transactions on Networking, to appear.

Modeling and Analysis of Generalized Slotted-Aloha MAC Protocols in Cooperative, Competitive and Adversarial Environments. Proceedings of IEEE International Conference on Distributed Computing Systems (ICDCS 06).

My research: future interests

Non-cooperative Game Theory

Mechanism Design: e.g. Tax Policy, Auction Theory

Coalition Game Theory

Implementation: Algorithm, Protocol Design, Stability and

Convergence Analysis

Micro-economics and Game Theory

Distributed Systems and Networks

Algorithmic Game Theory

Algorithmic Mechanism Design

Modeling: Optimization, Stochastic Process

Network Economics

Interdisciplinary research


– What’s the solution? ISPs don’t know, even with best intentions.– Answer: The Shapley value (Coalition Game)– How to find it? Complex ISPs structure, computationally expensive.– Result: Closed-form sol. and Dynamic Programming (Computer Sci.)– How to implement? Need to be implementable for ISPs.– Implication: New bilateral settlements (Operations)



– Answer: The Shapley mechanism (Mechanism design)

– Result 1: Incentives for optimal routes and interconnection (Behaviors)


– Result: Optimal global Nash equilibrium (Non-cooperative Game)

My research: future research problems

• Economics-related problems:– Facilitate P2P traffic on the Internet

– Network Neutrality

• Networking problems:– Incentive multicast protocols

– Wireless mesh networks

• Problems in other fields– Graph theory

– Distributed database system

– E-commerce, social networks

Marginal contribution of ISP i to set of ISPs S: Di(S).

The Shapley value mechanism j

Profit v(S) is defined on any subset of ISPs

Profit = Revenue - Cost

Revenue

Routing cost Profit: v(S)

x22/4

x72/4

x42/8 x5

2/8

x12/16

x82/16

1

v( ) = 0v( ) =0.8125

x62/16

v( ) = 0.625

x32/16

1/2

1/2

D ( ) = v( ) -v( ) = 0.1875

v( ) - v( ) = 0.625D ( ) =

j( )=2.4/6=0.4Empty

S

Empty

1N! ∈

∑ Di (S(,i))ji =

D (S(, ))

v( )=0

v( )=0.2v( )-

v( )-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 j

General Statement of Research

• Problem: – Individual objectives do not align with global objectives.– Economic incentives fail the engineering design goals of Internet.

• Objective: Reconcile individual incentives with global objectives.

• Approach: Design an economic mechanism– to address individual incentives,– to achieve global objectives.

Global Objectives (Engineering

Goals)EfficiencyFairness …

High ProfitLow Cost …

Individual Objectives (Economic Incentives)Economic

Mechanism

A Short Recap

• What have we done? – A Macro perspective– A central authority’s view to distribute profit among ISPs

and make appropriate settlements.

• What are we going to do? – A Micro perspective– Analysis of ISP selfish behaviors and strategies and their

effects on the entire network.

• Questions to answer– How will ISPs behave if the profits are distributed

according to the Shapley value solution?– How does that affect the entire network?

Network Economics and ISP Settlement Problems Tianbai Ma Department of Electrical Engineering...

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