The Public Option: A non-regulatory alternative to Network Neutrality - - PowerPoint PPT Presentation

The Public Option: A non-regulatory alternative to Network Neutrality

Richard Ma

School of Computing National University of Singapore

Joint work with Vishal Misra (Columbia University)

The 2nd Workshop on Internet Economics

Highlights

 A more realistic equilibrium model of

content traffic, based on

 User demand for content  System protocol/mechanism

 Game theoretic analysis on user utility

under different ISP market structures:

 Monopoly, Duopoly & Oligopoly

 Regulatory implications for all scenarios

and the notion of a Public Option

𝝂

 𝜈: capacity of a single access ISP  𝑁: # of users of the ISP (# of active users)  𝒪: set of all content providers (CPs)  𝜇𝑗: throughput rate of CP 𝑗 ∈ 𝒪

Three-party model (𝑁, 𝜈, 𝒪)

⋮

𝑵

⋮ 𝒪 𝝁𝒋

User-side: 3 Demand Factors

 Unconstrained throughput 𝜄𝑗

 Upper-bound, achieved under unlimited capacity  E.g. 5Mbps for Netflix

 Popularity of the content 𝛽𝑗

 Google has a larger user base than other CPs.

 Demand function of the content 𝑒𝑗(𝜄𝑗)

 Percentage of users still being active under the

achievable throughput 𝜄𝑗 ≤ 𝜄𝑗

Unconstrained Throughput 𝜇𝑗

User size 𝑵(= 𝟐𝟏) (Max) Throughput 𝜾 𝒋(= 𝟖𝑳𝒄𝒒𝒕) Content unconstrained throughput 𝝁 𝒋 = 𝜷𝒋𝑵𝜾 𝒋(= 𝟓𝟑𝑳𝒄𝒒𝒕) Content popularity 𝜷𝒋(= 𝟕𝟏%)

Demand Function 𝒆𝒋 𝜾𝒋

achievable throughput

𝜾𝒋 demanding # of users 𝜷𝒋𝑵𝒆𝒋 𝜾𝒋

𝜷𝒋𝑵

𝜾 𝒋

 Assumption 1: 𝑒𝑗 𝜄𝑗 is continuous and

non-decreasing in 𝜄𝑗 with 𝑒𝑗 𝜄𝑗 = 1.

 More sensitive to throughput  Throughput of CP i:

𝝁𝒋 𝜾𝒋 = 𝜷𝒋𝑵𝒆𝒋 𝜾𝒋 𝜾𝒋

Demand Function 𝒆𝒋 𝜾𝒋

achievable throughput

𝜾𝒋 demanding # of users 𝜷𝒋𝑵𝒆𝒋 𝜾𝒋

𝜷𝒋𝑵

𝜾 𝒋

System Side: Rate Allocation

 Axiom 1 (Throughput upper-bound)

𝜄𝑗 ≤ 𝜄 𝑗

 Axiom 2 (Work-conserving)

𝜇𝒪 = 𝜇𝑗

𝑗∈𝒪

= min 𝜈, 𝜇 𝑗

𝑗∈𝒪

 Axiom 3 (Monotonicity)

𝜄𝑗 𝑁, 𝜈2, 𝒪 ≥ 𝜄𝑗 𝑁, 𝜈1, 𝒪 ∀ 𝜈2 ≥ 𝜈1

Uniqueness of Rate Equilibrium

 Theorem (Uniqueness): A system (𝑁, 𝜈, 𝒪)

has a unique equilibrium {𝜄𝑗 ∶ 𝑗 ∈ 𝒪} (and therefore {𝜇𝑗 ∶ 𝑗 ∈ 𝒪}) under Assumption 1 and Axiom 1, 2 and 3. User demand: {𝜄𝑗} → {𝑒𝑗} Rate allocation: μ, 𝑒𝑗 → {𝜄𝑗}  Rate equalibrium: {𝜄𝑗

∗}, {𝑒𝑗 ∗}

ISP Paid Prioritization

ISP Payoff: 𝑑 𝜇𝑗

𝑗∈𝒬

= 𝑑𝜇𝒬

$𝒅/unit traffic $𝟏

Premium Class Ordinary Class Capacity Charge

𝝀𝝂 (𝟐 − 𝝀)𝝂 𝑵, 𝝀𝝂, 𝓠 𝑵, 𝟐 − 𝝀 𝝂, 𝓟

Monopolistic Analysis

 Players: monopoly ISP 𝐽 and the set of CPs 𝒪  A Two-stage Game Model 𝑁, 𝜈, 𝒪, 𝐽

 1st stage, ISP chooses 𝑡𝐽 = (𝜆, 𝑑) announces 𝑡𝐽.  2nd stage, CPs simultaneously choose service

classes reach a joint decision 𝑡𝒪 = (𝒫, 𝒬).  Outcome: set 𝒬 of CPs shares capacity 𝜆𝜈

and set 𝒫 of CPs share capacity 1 − 𝜆 𝜈.

Utilities (Surplus)

 ISP Surplus: 𝐽𝑇 = 𝑑

𝜇𝑗

𝑗∈𝒬

= 𝑑𝜇𝒬;

 Consumer Surplus: 𝐷𝑇 =

𝜚𝑗𝜇𝑗

𝑗∈𝒪

 𝜚𝑗 : per unit traffic value to the users

 Content Provider:

 𝑤𝑗 : per unit traffic profit of CP 𝑗

𝑣𝑗 𝜇𝑗 = 𝑤𝑗𝜇𝑗 𝑤𝑗 − 𝑑 𝜇𝑗 if 𝑗 ∈ 𝒫, if 𝑗 ∈ 𝒬.

Type of Content

Value to users 𝝔𝒋 Profitability of CP 𝒘𝒋

Monopolistic Analysis

 Players: monopoly ISP 𝐽 and the set of CPs 𝒪  A Two-stage Game Model 𝑁, 𝜈, 𝒪, 𝐽

 1st stage, ISP chooses 𝑡𝐽 = (𝜆, 𝑑) announces 𝑡𝐽.  2nd stage, CPs simultaneously choose service

classes reach a joint decision 𝑡𝒪 = (𝒫, 𝒬).  Theorem: Given a fixed charge 𝑑, strategy

𝑡𝐽 = (𝜆, 𝑑) is dominated by 𝑡𝐽

′ = (1, 𝑑).

• The monopoly ISP has incentive to allocate

all capacity for the premium service class.

Utility Comparison: Φ vs 𝛺

Ψ = 𝐽𝑇/𝑁 𝜉 = 𝜈/𝑁 Φ = 𝐷𝑇/𝑁

Regulatory Implications

 Ordinary service can be made “damaged

goods”, which hurts the user utility.

• Implication: ISP should not be allowed to

use non-work-conserving policies (𝜆 cannot be too large).

 Should we allow the ISP to charge an

arbitrarily high price 𝑑?

High price 𝑑 is good when

Value to users 𝝔𝒋 Profitability of CP 𝒘𝒋

High price 𝑑 is bad when

Value to users 𝝔𝒋 Profitability of CP 𝒘𝒋

Oligopolistic Analysis

 A Two-stage Game Model 𝑁, 𝜈, 𝒪, ℐ

 1st stage: for each ISP 𝐽 ∈ ℐ chooses 𝑡𝐽 = (𝜆𝐽, 𝑑𝐽)

simultanously.

 2nd stage: at each ISP 𝐽 ∈ ℐ, CPs choose service

classes with 𝑡𝒪

𝐽 = (𝒫𝐽, 𝒬𝐽)

 Difference with monopolistic scenarios:

 Users move among ISPs until the per user surplus

Φ𝐽 is the same, which determines the market share of the ISPs

 ISPs try to maximize their market share.

Duopolistic Analysis

𝓠 𝓟 𝓞

ISP 𝑱 with 𝒕𝑱 = (𝝀, 𝒅) ISP 𝑲 with 𝒕𝑲 = (𝟏, 𝟏)

Duopolistic Analysis: Results

 Theorem: In the duopolistic game, where an

ISP 𝐾 is a Public Option, i.e. 𝑡𝐾 = (0, 0), if 𝑡𝐽 maximizes the non-neutral ISP 𝐽’s market share, 𝑡𝐽 also maximizes user utility.

• Regulatory implication for monopoly cases:

Oligopolistic Analysis: Results

 Theorem: Under any strategy profile 𝑡−𝐽, if

𝑡𝐽 is a best-response to 𝑡−𝐽 that maximizes market share, then 𝑡𝐽 is an 𝜗–best-response for the per user utility Φ.

• The Nash equilibrium of market share is an

𝜗-Nash equilibrium of user utility.

• Oligopolistic scenarios:

Regulatory Preference

Monopoly Oligopoly

ISP market structure User Utility