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17
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







2

Vishal Anand

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.

Vishal Anand 3

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).

Vishal Anand 4

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.

Vishal Anand 5

The Maximum Profitability Problem

 Given:

– a set of connection requests, N.

– a network topology.

– earnings (revenue) Ei associated with each

connection request, i.

– cost of using any wavelength on a link l, Cl.

 Solve the RWA problem to maximize the

profit, P = Total Earnings - Total Costs.

Vishal Anand 6

 Maximizing profit problem is a more

general formulation.

– If Ei=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 Ei=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.

Vishal Anand 7

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.

8

Vishal Anand

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.

9

Vishal Anand

– 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.



10

Vishal Anand

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.





11

Vishal Anand

Comparison of the heuristics









 MaxPro performs the best.

 Better than a minimizing cost heuristic.

12

Vishal Anand

Integer Linear Model

 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.

13

Vishal Anand

 Objective function









 Subject to:







– The total number of lightpaths established between a node pair

should not exceed the number of requests between that node pair.



14

Vishal Anand

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.

15

Vishal Anand

Comparison of Maxpro with ILP









 MaxPro obtains on the average 90% of the

results got from the ILP(optimal profit).

16

Vishal Anand

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.

17

Vishal Anand



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