Artificial Intelligence Based Dynamic Wavelength Grouping for QoS in Optical Packet Switched Networks
Keywords:
Optical packet switching, quality of service, Linear Regression ModelAbstract
In optical packet switching (OPS) networks wavelengths are shared on optical links and data packets are multiplexed statistically in all-optical domain. Quality of service concerns about management of resources and traffic control to deliver improved services to specific traffic classes. An artificial Intelligence-based dynamic wavelength grouping (AIDWG) scheme is proposed for OPS. In this scheme, available wavelengths are partitioned dynamically by Linear Regression Model (LRM) and allocated to traffic service classes at each network link. AIDWG tracks the load, blocking, wait time and utilization of each traffic class and schedules optical packets according to the assigned group of wavelengths. IBKSim simulator is used to examine the performance of NSFNet topology. DWG beats its previous static version(SWG) by a significant factor. Due to the flexibility, the proposed AIDWG technique gives good results in Blocking and Throughput even when the load share of one class is significantly less than other classes of traffic.
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