Two-Market Inter-domain Bandwidth Contracting

Anusha Uppaluri, University of Nevada, Reno(anusha.uppaluri@gmail.com)

Praveen Kumar, Rensselaer Polytechnic Institute Murat Yuksel, University of Nevada, Reno

Aparna Gupta, Rensselaer Polytechnic InstituteKoushik Kar, Rensselaer Polytechnic Institute

Industrial Engineering Research Conference, IERC, 61st Annual Conference & Expo, Reno, Nevada, May 21-25, 2011.

1

Overview• Introduction• Problem Formulation

– Network Model– Single Edge – to – Edge Contract Link– Multiple Edge – to – Edge Contract Links

• Simulation Experiments– Single Edge – to – Edge Link– Multiple Edge – to – Edge Links

• Network Setup• Results

• Conclusion and Future Work

2

Introduction

• Migration of data rich applications indicate that the increasing demand for bandwidth is unlikely to vanish

• Managing bandwidth allocation to customers presents a major challenge and received a lot of attention

• Many approaches involving advanced techniques for achieving efficient contracting among ISPs have been explored

3

Introduction (contd..)

• Crucial handicap of existing inter – ISP economics is coarse granularity of contracts

• Precursor to realization of more dynamic & automated contracting is sufficient motivation for ISPs to invest and install necessary tools & protocols

• Question focused on : how much benefit there is if the contracts were classified into simple two market regime, highly dynamic and long time scale durable

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Introduction (contd..)

• Also, an important issue is the management of risks in ISPs investments

• Though an automated and dynamic way of establishing contracts will enable ISPs to flexibly allocate their resources several questions arise:– When and where to advertise a new contract– How to assess the risks involved and reflect

them on contracting parameters – How to divide links between different types

of contracts

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Introduction (contd..)

• Model and formulate revenue maximization problem by considering the constraints imposed by correlation among contract links

• Through a detailed simulation several insights on optimal reservation levels for the two types of contracts are provided

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Problem formulation

Contract switched Internet architecture considered7

Problem formulation(contd..)

• Edge – to – edge contract links are advertisable contracts between pairs of ingress and egress routers

• The Capacity of a contract link is equal to the minimum of the capacities of the physical links used to construct the contract link

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Problem formulation(contd..)

• Capacity of the contract links must be segmented between short – term and long – term contracts

• There is enough demand for long – term contracts while the demand for short – term contracts is stochastic

• Revenue from unit demand for short – term contracts per unit time is higher than Revenue from unit demand for long – term contracts per unit time

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Single Edge- to- Edge Contract Link

• Single edge – to – edge contract link is considered• Enough demand for long – term contracts is

assumed. Bandwidth allotted for long – term contracts is always used

• Bandwidth available for short – term contracts may or may not be used

• ISP must choose optimal value for bandwidth reserved towards long – term contracts so that total expected revenue per unit time is maximized

10

•

Single Edge- to- Edge Contract Link(contd..)

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Revenue obtained from long - term

contracts per unit time

Revenue obtained from short – term contracts per unit

time

Bandwidth reserved for long – term

contracts

Capacity of the contract

link

Multiple Edge- to- Edge Links

• Assuming several edge – to – edge links in ISP’s network

• Edge – to – edge contract links share physical links which impose constraints on bandwidth reserved for long – term contracts of these contract links

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•

Multiple Edge- to- Edge Links (contd..)

Bandwidth reserved for long –

term contracts

Capacity of the physical links used to construct the

contract link

13

•

= Revenue form long term contracts per unit time

Multiple Edge- to- Edge Links (contd..)

Revenue from long –term

contracts per unit time

Sum of revenue obtained from long term

contracts on multiple contract links

14

•

 

Multiple Edge- to- Edge Links (contd..)Revenue

obtained from short term

contracts per unit timeMinimum of

Short term demand and

residual capacity

Reservation for short – term contracts on contract linkReservation for short – term

contracts on a contract link

Remaining capacity of

physical link l

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Multiple Edge- to- Edge Links (contd..)

•

16

 

Revenue from long – term

contracts per unit time

Revenue from short – term contracts per

unit timeBandwidth reserved

towards long term contracts

Capacity of contract link

Bandwidth reserved for long –

term contracts

Capacity of the physical links used to construct the

contract link

Simulation Experiments

Single edge – to – edge link• Capacity of single edge – to – edge contract link is

set to 10• Two distributions of short term demand

– Uniform distribution between 0 and 10– Truncated Gaussian distribution in the interval

[0,10] with mean 5 and standard deviation 1

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Simulation Experiments(contd..)

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Optimal long term reservation on contract link is shown. PL is increased from 0 and PS is fixed at 10

Optimal long term reservation on

contract link on Y-axis

PL is being increased from 0 to

10 on X-axis

Graph for truncated Gaussian

distribution

Graph for uniform

distribution

Multiple Edge – to – Edge Links

Network Setup• Real topology map of GEANT ISP with 23 routers

is used. 3 ingress & 3 egress routers are chosen. Nine edge- to- edge contract links are considered

• Capacity of physical links is set to 10 and so the capacity of contract link (Bie) is 10.

• Short term demand is taken to be uniformly distributed between 0 and 10

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Results

Maximum total revenue, maximum long term revenue and maximum short term revenue are shown. PS is set to 10

20

PL is being increased

from 1 to 10 on X-axis

Maximum total revenue on Y-

axis

PL≤5 then PL is not high enough to

generate significant long term revenue

PL>5 then long – term contracts

generate higher revenue

Optimal reservation levels on nine links when PL=5 and PS=10 & PL=10 and PS=10

Results(contd..)

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PL=5 and PS=10 PL=10 and PS=10

Contract links listed on X- axis

Contract link capacity on Y-axis

Contract links listed on X- axis

Contract link capacity on Y-axis

Increasing PL increases long -

term reservation levels

Long term reservation levels on 1,6,7 remain zero at all times

Conclusion and Future Work

• Revenue maximization problem was formulated for an ISP which wants to participate in two segments of bandwidth markets

• The level and distributional characteristics of short – term demand and interactions among contract links are key determinants

• In the future, possibility of multiple paths underlying a given single contract link instead of single path will be considered

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Queries?

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