1. Two-Market Inter-domain Bandwidth Contracting
Anusha Uppaluri, University of Nevada, Reno
Praveen Kumar, Rensselaer Polytechnic Institute
Murat Yuksel, University of Nevada, Reno
Aparna Gupta, Rensselaer Polytechnic Institute
Koushik Kar, Rensselaer Polytechnic Institute
Industrial Engineering Research Conference, IERC,
61st Annual Conference & Expo,
Reno, Nevada, May 21-25, 2011.

2. 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

3. 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

4. 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

5. 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

6. 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

7. Contract switched Internet architecture considered
Problem formulation
Contract switched Internet architecture considered

8. 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

9. 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

10. 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

11. Single Edge- to- Edge Contract Link(contd..)
Revenue obtained from short – term contracts per unit time
Revenue obtained from long - term contracts per unit time
Capacity of the contract link
Bandwidth reserved for long – term contracts

12. 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

13. Multiple Edge- to- Edge Links (contd..)
Capacity of the physical links used to construct the contract link
Bandwidth reserved for long – term contracts

14. Multiple Edge- to- Edge Links (contd..)
Sum of revenue obtained from long term contracts on multiple contract links
Revenue from long –term contracts per unit time
= Revenue form long term contracts per unit time

15. Multiple Edge- to- Edge Links (contd..)
Revenue obtained from short term contracts per unit time
Reservation for short – term contracts on contract link
Minimum of Short term demand and residual capacity
Reservation for short – term contracts on a contract link
Remaining capacity of physical link l

16. Multiple Edge- to- Edge Links (contd..)
Revenue from long – term contracts per unit time
Revenue from short – term contracts per unit time
Bandwidth reserved towards long term contracts
Capacity of contract link
Capacity of the physical links used to construct the contract link
Bandwidth reserved for long – term contracts

17. 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

18. Simulation Experiments(contd..)
Graph for uniform distribution
Optimal long term reservation on contract link on Y-axis
Graph for truncated Gaussian distribution
PL is being increased from 0 to 10 on X-axis
Optimal long term reservation on contract link is shown. PL is increased from 0 and PS is fixed at 10

19. 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

20. Results PL>5 then long – term contracts generate higher revenue
Maximum total revenue on Y-axis
PL≤5 then PL is not high enough to generate significant long term revenue
PL is being increased from 1 to 10 on X-axis
Maximum total revenue, maximum long term revenue and maximum short term revenue are shown. PS is set to 10

21. Results(contd..) PL=5 and PS=10 PL=10 and PS=10
Contract link capacity on Y-axis
Increasing PL increases long -term reservation levels
Contract link capacity on Y-axis
Long term reservation levels on 1,6,7 remain zero at all times
Contract links listed on X- axis
Contract links listed on X- axis
Optimal reservation levels on nine links when PL=5 and PS=10 & PL=10 and PS=10

22. 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

23. Queries?