Optimal Pricing in Finite Server Systems Ashok Krishnan K.S. a , - - PowerPoint PPT Presentation

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Optimal Pricing in Finite Server Systems Ashok Krishnan K.S. a , - - PowerPoint PPT Presentation

Optimal Pricing in Finite Server Systems Ashok Krishnan K.S. a , Chandramani Singh a , Siva Theja Maguluri b , Parimal Parag a a Indian Institute of Science b Georgia Institute of Technology Introduction The Problem 1 5 servers, 2 busy 2 3 4


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SLIDE 1

Optimal Pricing in Finite Server Systems

Ashok Krishnan K.S.a, Chandramani Singha, Siva Theja Magulurib, Parimal Paraga

aIndian Institute of Science bGeorgia Institute of Technology

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SLIDE 2

Introduction

The Problem

1 2 3 4 5 5 servers, 2 busy

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SLIDE 3

Introduction

The Problem

1 2 3 4 5 5 servers, 2 busy new job V

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SLIDE 4

Introduction

The Problem

1 2 3 4 5 5 servers, 2 busy new job V price p2

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SLIDE 5

Introduction

The Problem

1 2 3 4 5 5 servers, 2 busy new job V price p2 V < p2

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SLIDE 6

Introduction

The Problem

1 2 3 4 5 5 servers, 3 busy new job V price p2 V ≥ p2

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SLIDE 7

Introduction

The Problem

1 2 3 4 5 5 servers, 3 busy

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SLIDE 8

Introduction

The Problem

1 2 3 4 5 5 servers, 3 busy new job V price p3

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SLIDE 9

Introduction

The Problem

1 2 3 4 5 5 servers, 3 busy new job V price p3 p0, p1, .., p4?

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SLIDE 10

Introduction

Previous Work and Our Setting

Social optimum vs Revenue Maximization

Naor ’69, Chen ’01, Borgs ’14

Homogeneous vs heterogeneous customers

Whang ’90, Shimkin ’00, Mandelbaum ’02

Single vs Multi Servers

Haviv ’94, Bradford ’96, Dumas ’11

Our setting:

Revenue maximization Heterogeneous customers Multi server system

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SLIDE 11

System Model

System Model

1 2 3 4 5 Poisson λ i.i.d. V ∼ G exp(µ) price vector (p0, p1, p2, p3, p4)

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SLIDE 12

System Model

State Evolution

1 2 3 4 5 State 0

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SLIDE 13

System Model

State Evolution

1 2 3 4 5 1 State 1

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SLIDE 14

System Model

State Evolution

1 2 3 4 5 arrival value V 1 2 3 4 5 if V ≥ p1

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SLIDE 15

System Model

State Evolution

1 2 3 4 5 1 2 3 4 5 service completion

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SLIDE 16

System Model

State Evolution

1 2 3 4 5 1 2 3 4 5 1 2 λ P(V ≥ p1) 2µ

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SLIDE 17

System Model

State evolution

1 2 3 4 5 λ0 λ1 µ λ2 2µ λ3 3µ λ4 4µ 5µ λi = λP(V ≥ pi) = λ(1 − G(pi)) = λG(pi) Gives stationary distribution π

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SLIDE 18

System Model

Revenue

λ i busy servers price pi w.p. πi joins w.p. G(pi) Revenue =λ K−1

i=0 πiG(pi)pi

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SLIDE 19

System Model

The Infinite Server Case

1 2 3 4 5 Infinite Servers Revenue =λ ∞

i=0 πiG(pi)pi

≤ λG(p∗)p∗

i πi

p∗ = arg max pG(p)

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SLIDE 20

System Model

A Sub-Optimal Scheme

1 2 3 4 5 Uniform Pricing All states have same price p∗

5 = arg max pG(p)(1 − π5(p))

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SLIDE 21

Optimal Solution and its properties

Optimal Price

1 2 3 4 0.5 1 1.5 2 p∗

5

number of busy servers Price

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SLIDE 22

Optimal Solution and its properties

Properties of the Optimal Solution

10 15 20 25 30 2 4 6 8 arrival rate Revenue 10 15 20 25 30 0.2 0.25 0.3 0.35 0.4 arrival rate Revenue/arrival rate

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SLIDE 23

Optimal Solution and its properties

Properties of the Optimal Solution

1 2 3 4 5 5 6 7 8 9 service rate Revenue 1 2 3 4 5 2 3 4 5 6 service rate Revenue/service rate

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SLIDE 24

Optimal Solution and its properties

Properties of the Optimal Solution

3 4 5 6 7 6 7 8 9 number of servers Revenue 3 4 5 6 7 1.2 1.4 1.6 1.8 2 number of servers Revenue/server

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SLIDE 25

Optimal Solution and its properties

Properties of the Optimal Solution

3 4 5 6 7 1 1.2 1.4 1.6 1.8 2 p∗ number of servers Price p0 p1 p2

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SLIDE 26

Optimal Solution and its properties

Revenue Gain

0.5 1 5 10 2 4 6 load Revenue Rate p∗ p∗

5

P

Figure: Revenue rate as a function of load

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SLIDE 27

Summary

Summary

Analysis of system with heterogeneous customers Solution to the server pricing problem for revenue maximization Uniform pricing is optimal for infinite server system Analytical MDP solution to obtain the optimal pricing for a finite server system Two simple heuristic algorithms for pricing a finite server system Properties of optimal pricing for finite server systems Performance comparison between the optimal and heuristic algorithms for finite server systems