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Two-Market Inter-domain Bandwidth Contracting

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 Institute

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Two-Market Inter-domain Bandwidth Contracting

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  1. 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 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. 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 contractsof 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. PLis increased from 0 and PSis 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?

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