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PROFITABLE CONNECTION ASSIGNMENT IN ALL OPTICAL WDM NETWORKS VISHAL ANAND LANDER (Lab. for Advanced Network Design, Evaluation and Research) In collaboration.

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Presentation on theme: "PROFITABLE CONNECTION ASSIGNMENT IN ALL OPTICAL WDM NETWORKS VISHAL ANAND LANDER (Lab. for Advanced Network Design, Evaluation and Research) In collaboration."— Presentation transcript:

1 PROFITABLE CONNECTION ASSIGNMENT IN ALL OPTICAL WDM NETWORKS VISHAL ANAND LANDER (Lab. for Advanced Network Design, Evaluation and Research) In collaboration with: Tushar Katarki and Chunming Qiao CSE Dept., SUNY at Buffalo

2 2 4 Introduction 4 Related work 4 Maximum Profitability Problem 4 Concluding remarks 4 Questions and discussion Vishal Anand Outline

3 3 Introduction 4 Optical WDM networks - future backbone for wide area networks. 4 Physical Topology - Optical wavelength routers connected by fiber links. 4 Lightpath or connection - Path between two end nodes and a wavelength on that path. 4 No wavelength conversion - Any lightpath uses the same wavelength on all the links its path spans. Vishal Anand

4 4 The RWA(Routing & Wavelength Assignment) Problem 4 Given : –a network topology –a set of traffic demands (or connection requests). 4 Determine the routes and wavelengths to use so as to satisfy the demands. 4 The RWA problem is usually solved to optimize some specified objective(s). Vishal Anand

5 5 Previous and related work 4 Example objectives –Minimize network-wide packet delay (e.g. number of hops). –Maximize throughput (e.g. number of lightpaths). –Maximize allowable capacity upgrade or scalability (for future traffic demands). 4 Minimizing cost (network resources used) can also be an important objective. 4 For a bandwidth broker (or carrier) maximizing profits is most important. Vishal Anand

6 6 The Maximum Profitability Problem 4 Given: –a set of connection requests, N. –a network topology. –earnings (revenue) E i associated with each connection request, i. –cost of using any wavelength on a link l, C l. 4 Solve the RWA problem to maximize the profit, P = Total Earnings - Total Costs. Vishal Anand

7 7 4 Maximizing profit problem is a more general formulation. –If E i =E, for each connection/lightpath i (i.e., all connections have equal earnings) OR if n=N (i.e., all the connection requests have to be satisfied) then the problem is same as the minimizing cost problem. –If E i =E and if all connections/lightpaths have equal costs. Then the problem is the same as maximizing throughput problem. 4 Hence a more direct study of the maximizing profit problem is necessary. Vishal Anand

8 8 Network Model 4 Network topology considered: 16 node NSFNET. 4 Cost of using each wavelength on a link, is the same, but varies from link to link. 4 No wavelength conversion capabilities at any of the nodes. 4 Number of wavelengths on each link in the network is the same. Vishal Anand

9 9 Heuristic based approach 4 The RWA problem is known to be NP Hard and hence computationally intractable. 4 Maximizing profit heuristic: MaxPro –Find a cheapest path for each connection request and compute the profit. –Sort the requests in the order of decreasing profit and store in a list. –Satisfy connection requests in decreasing order of profit (a greedy approach). –If a connection request is satisfied. delete that connection from the sorted list. Vishal Anand

10 10 –If the cheapest path for a connection request is not available. Re-compute a new cheapest path for only that connection request. Compute the new profit for this connection request. Insert this connection into the sorted list depending on the profit. –Repeat till no other connection request can be satisfied. Vishal Anand

11 11 Results and Comparison 4 1) Results obtained from MaxPro compared with: –a minimizing cost heuristic –a random assignment heuristic 4 2) Results of Maxpro compared with the optimal results from integer linear program. Vishal Anand

12 12 Comparison of the heuristics 4 MaxPro performs the best. 4 Better than a minimizing cost heuristic. Vishal Anand

13 13 Integer Linear Model 4 Definitions: –W :Number of wavelengths on each link. –n, L :Number of nodes, links in the network. – :Earnings obtained by satisfying a connection request between nodes  and . – : Total number of alternate routes/paths available to reach node  from node . – : Cost of reaching node  from node  on route r. – : = 1, if link j is used by the route r between nodes  and , 0 otherwise. – : Number of connection requests between nodes  and . – : = 1, indicates that the connection between node  and  is routed on route r using wavelength k. Vishal Anand

14 14 4 Objective function 4 Subject to: –The total number of lightpaths established between a node pair should not exceed the number of requests between that node pair. Vishal Anand

15 15 And –The total number of lightpaths established on any link should not exceed the number of wavelength on that link. –A wavelength on a link can support at most one lightpath. –The Integrality constraint. Vishal Anand

16 16 Comparison of Maxpro with ILP 4 MaxPro obtains on the average 90% of the results got from the ILP(optimal profit). Vishal Anand

17 17 Summary and Future work 4 Formulated a RWA problem with the objective of maximizing the profit. 4 Proposed a maximizing profit heuristic. 4 Compared results of a profit maximizing heuristic with a minimizing cost heuristic and ILP. 4 Future work –Study the maximizing profit problem for the On-line traffic model. –Extend to cases where protection and restoration is required for the traffic. Vishal Anand


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