Soumya Sen, K. Yamauchi, Roch Guerin and Kartik Hosanagar

ESE, Wharton

University of Pennsylvania

ssoumya@seas.upenn.edu

www.seas.upenn.edu/~ssoumya

11th December, 2010. Ninth Workshop on E-business, WEB 2010, St. Louis, MO

The Impact of Re-provisioning on the Choice of Shared versus Dedicated Networks

Network Infrastructure Choice:Shared Versus Dedicated Networks

1. Problem Formulation

2. Model & Solution Methodology

3. Key Findings & Examples

4. Conclusions

Talk Outline

2

• Emergence of new services require: – Network provider has to decide between:

• Common (shared) Network Infrastructure• Separate (dedicated) Network Infrastructure

• Examples:– Facilities Management services & IT

• e.g. IT & HVAC systems

– Video and Data services• e.g. Internet & IPTV services

– Cloud Computing• e.g. Private (dedicated) cloud Vs Shared cloud

– Broadband over Power lines

• Lack of Framework to evaluate choices:– Ad-hoc decisions (AT&T U-Verse versus Verizon FiOS)– Manufacturing Systems Literature:

• Plant-product allocation, optimal resource allocation

Motivation

3

• News-Vendor Problem– Resource allocation when demand is uncertain– Need to add “Reprovisioning” phase to these models

• Plant-product allocation– How to allocate product demands to manufacturing plants– Effect of process flexibility in handling variable demand

• Jordan & Graves (1995), Graves & Tomlin (2003), E.K.Bish, Muriel, Biller (2005)

• Optimal Resource Allocation• Fine & Fruend (1990) – firm’s optimal investment in flexible and dedicated

resources• J.A.Van Mieghem (1998) – role of price margins and cost-mix differential

on flexibility benefits

• Our model focuses on the impact of reprovisioning, economies of scope, and identifies operational metrics for network design decision

Related Literature

4

• Two network services (technologies) – One existing (mature) service – One new service with demand uncertainty

• Sharing can create economies or diseconomies of scope in costs

• New service has demand uncertainty– Needs capacity provisioning

• before demand gets realized

– Dynamic resource “reprovisioning”• But some penalty will be incurred (portion of excess demand is lost)

– Technology advances allow Reprovisioning (e.g., using virtualization)

• How critical is reprovisioning ability in choosing network design?– Compare networks based on profits

Problem Formulation

5

Model Formulation

6

• Basic Model: A Two-Service Model

• Service 1 (existing service)• Service 2 (new service with

uncertain demand)

• Three-stage sequential decision process

• Compare Infrastructure choices based on expected profits

Reprovisioning Stage

Capacity Allocation Stage

Infrastructure Choice Stage

Solve backwards

Model Variables

7

Provider’s profit depends on:

Costs:

• Fixed costs

• Variable costs - grows with the number of subscribers (e.g. access equipment, billing)

• Capacity costs - incurred irrespective of how many users join (e.g. provisioning, operational)

Cost Component Service 1 Dedicated

Service 2 Dedicated

Shared

Fixed Costs cd1 cd2 cs

Contribution Margin(grows with each unit of realized demand)

pd1 pd2 ps1, ps2

Variable Costs(incurred irrespective of realized demand)

ad1 ad2 as1, as2

Gross Profit Margin = pi - ai , i={s2, d2}

Return on capacity = pi /ai

Solution (1): Reprovisioning Stage

8

• Service 2 revenue: (i={s2, d2} for Shared and Dedicated respectively)

i. when D2 ≤ Ki: Ri (D2 ≤ Ki) = pi D2 – ai Ki

ii. when D2>Ki:

Reprovisioning Ability:

• A fraction “α” of the excess demand can be accommodated

User contribution

Capacity cost

Ri (D2 > Ki) = (pi – ai )(Ki + α(D2 - Ki))

• A word about reprovisioning ability, α

– Independent of the magnitude of excess demand– Captures feasibility of and latency in securing additional resources– So what do α =0 and α =1 mean?

Solution (2): Capacity Allocation Stage

9

• Expected Revenue, E(Ri|Ki), for a given provisioned level Ki:

• Optimal Provisioning Capacity:

• For demand distribution ~U[0, D2max]:

max2

2

2

)()(

)()()(

22

0

22][

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K

Dii

K

DiiKi

i

i

i

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DdfKDRRE

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iii ap

DapK

)1(

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2

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2

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s

s

d

d

a

p

a

p

Solution (3): Infrastructure Choice Stage

10

• Dedicated Networks:

– Service 1 revenue:

– Service 2 revenue under optimal provisioning:

– Total profit:

• Shared Network:

• Infrastructure Choice:

– Common if , else separate

11111 )( dddd capD

22

2max222

2 )1(

)1(1

2

)(

dd

dddd ap

aDap

21 ddd

1111

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)1(

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Profit from Service 2

Profit from Service 1

sssss

ssss capD

ap

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2max222

ds

Choice of Infrastructure

11

• Impact of system parameters:– Varying cost parameters affect the choice of infrastructure

• Shared to Dedicated (or Dedicated to Shared)• Single threshold for switching n/w choice

– Surprisingly, ad-hoc “reprovisioning” ability also impacts in even more interesting ways!

• Common is preferred over separate when ds

Independent of provisioning decision

Depends on provisioning decision

Diff. in optimal capacity cost

h(α)=

Function of pi, ai, α, i={s2,d2}

2)()( *22

*22 ssdd KaKa

Analyzing the effect of α on h(α)

12

• Proposition 1: Increase in α benefits both shared and dedicated networks.

(i) if increases in α benefits shared (dedicated) n/w more than dedicated (shared)

(ii) if increases in α benefits shared (dedicated) more at low α and dedicated (shared) more at high α

• The value of h'(0) and h'(1) fully characterize the shape of h(α)

)0)1(,0)0((,0)1(,0)0( hhhh

)0)1(,0)0((,0)1(,0)0( hhhh

Gross Profit Margin

Return on Capacity

2222

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2

2

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:0)0(

ssdd

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ss

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Results: Impact of Reprovisioning

13

GPMded (pd2-ad2) is sufficiently lower than GPMshr (ps2-as2)GPMded > GPMshr i.e. (pd2-ad2) >(ps2-as2) and ROCded <ROCshr i.e. (pd2/ad2) <(ps2/as2) GPMded > GPMshr i.e. (pd2-ad2) >(ps2-as2) and ROCded >ROCshr i.e. (pd2/ad2) >(ps2/as2)

• Developed a generic model that captures economies and diseconomies of scope between shared and dedicated networks

• Reprovisioning can affect the outcome in non-intuitive ways– Validates the need for models to incorporate this feature– Yields guidelines on how reprovisioning affects choice of network infrastructure

• Identified key operational metrics to consider– Provides decision guideline

• Robustness:– Non-uniform demand distribution (positively & negatively skewed β-distribution)– Economies and diseconomies of scale– Different reprovisioning abilities for shared and dedicated networks (α1, α2 ≠ α)

Conclusions

14

Thank You!