PROFITABLE CONNECTION ASSIGNMENT IN ALL OPTICAL WDM NETWORKS VISHAL ANAND

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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 with:

Tushar Katarki and Chunming Qiao

CSE Dept., SUNY at Buffalo

Outline

 Introduction

 Related work

 Maximum Profitability Problem

 Concluding remarks

 Questions and discussion

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Introduction

 Optical WDM networks - future backbone for wide area networks.

 Physical Topology - Optical wavelength routers connected by fiber links.

 Lightpath or connection - Path between two end nodes and a wavelength on that path.

 No wavelength conversion - Any lightpath uses the same wavelength on all the links its path spans.

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The RWA(Routing & Wavelength

Assignment) Problem

 Given :

– a network topology

– a set of traffic demands (or connection requests).

 Determine the routes and wavelengths to use so as to satisfy the demands.

 The RWA problem is usually solved to optimize some specified objective(s).

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Previous and related work

 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).

 Minimizing cost (network resources used) can also be an important objective.

 For a bandwidth broker (or carrier) maximizing profits is most important.

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The Maximum Profitability Problem

 Given:

– a set of connection requests, N.

– a network topology.

– earnings (revenue) E i connection request, i .

associated with each

– cost of using any wavelength on a link l , C l

.

 Solve the RWA problem to maximize the profit, P = Total Earnings - Total Costs .

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 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.

 Hence a more direct study of the maximizing profit problem is necessary.

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Network Model

 Network topology considered: 16 node

NSFNET.

 Cost of using each wavelength on a link , is the same, but varies from link to link.

 No wavelength conversion capabilities at any of the nodes.

 Number of wavelengths on each link in the network is the same.

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Heuristic based approach

 The RWA problem is known to be NP Hard and hence computationally intractable.

 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.

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– 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.

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Results and Comparison

 1) Results obtained from MaxPro compared with:

– a minimizing cost heuristic

– a random assignment heuristic

 2) Results of Maxpro compared with the optimal results from integer linear program.

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Comparison of the heuristics

 MaxPro performs the best.

 Better than a minimizing cost heuristic.

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Integer Linear Model

 Definitions:

– W :Number of wavelengths on each link.

– n, L :Number of nodes, links in the network .

E



:Earnings obtained by satisfying a connection request between nodes

 and

.

– R



: Total number of alternate routes/paths available to reach node

 from node

.

C r



: Cost of reaching node

 from node

 on route r.

– rj l



: = 1, if link j is used by the route r between nodes

 and

, 0 otherwise.

– d



: Number of connection requests between nodes

 and

.

– x rk

 rk : = 1, indicates that the connection between node

 and

 is routed on route r using wavelength k.

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 Objective function max n n

E



R  W  

 

1

 

1 r

1 k

1 x rk



R  r

 

1

C r

 k

W

1 x rk



 Subject to:

R  r

W 

1 k

1 x rk



 d



 

,

The total number of lightpaths established between a node pair should not exceed the number of requests between that node pair.

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And

R  n n 

 

1

 

1 r

1 l rj

 k

W 

1 x rk



W

 j

1 ,..., L

– The total number of lightpaths established on any link should not exceed the number of wavelength on that link.

n n R  

 

1

  

1 l rj

 x rk



1

 j

1 ,..., L ,

 k

1 ,..., W

– A wavelength on a link can support at most one lightpath.

x rk



 

– The Integrality constraint.

 

,

, r , k

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Comparison of Maxpro with ILP

 MaxPro obtains on the average 90% of the results got from the ILP(optimal profit).

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Summary and Future work

 Formulated a RWA problem with the objective of maximizing the profit.

 Proposed a maximizing profit heuristic.

 Compared results of a profit maximizing heuristic with a minimizing cost heuristic and ILP.

 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.

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