Evaluation of Hidden Markov Model based adaptive Provisioning of optical burst switching Networks Amenable for Upgradation to Green Flexigrid Networks

Abstract

Catering to the evolving bandwidth-on-demand applications requires flexible provisioning architectures that ensure fairness to both high end and low end users of internet. Dynamic classification of network path s into long and short, based on traffic dependent connecti on holding times and a wavelength allocation from different subsets for these categories is a necessi ty for implementing energy saving hybrid switching, loss recovery and flexi grid bit rate variable schemes. Therefore, this study evaluates such a scheme of d ynamic classification based on HMM predicted connection-holding times with tightly integrated adaptive burst sizing and segregated wavelength allocation for lon g and short categories. Simulation study of a 28 no de OBS network shows that this coupled scheme reduces delays and results in throughput improvement of 67% for long and 12% for short traffic over schemes tha t employ adaptive burst sizing based on number of a ctive traffic flows and independent wavelength assignment schemes.