An Analytical Model of Spectrum Fragmentation in a Two-Service Elastic Optical Link

Abstract

Elastic Optical Networks (EONs) enable optical circuits to be assigned distinct numbers of spectrum slices. Individual circuits can then be assigned an optimal number of slices to best match their target transmission rates. A well-known drawback of EONs is spectrum fragmentation and its resulting uneven blocking probability, which circuit requests experience when the available spectrum slices in the fiber are insufficient or not contiguous. Capturing this spectrum fragmentation problem analytically is a challenging problem. Not surprisingly, most of the existing studies at this time mainly use simulationbased techniques to quantify blocking probability in EONs. In this paper, the authors present a Markov Chain (MC) model that attempts to characterize the fragmentation problem in a simplified scenario, i.e., only two types of circuit services are allowed over a single fiber link. Despite its limited scope, this initial analytical effort is able to accurately capture the nonmonotonic behavior of the blocking probability in EONs for the first time.

A Vectored Fragmentation Metric for Elastic Optical Networks

“…We observed the evolution of average network spectrum utilization (Utilization in figs. 6,7,8), the average link-based external fragmentation metric (L-EFM), the average blocked requests to total requests ratio (BR/TR), and the average adapted vectored-fragmentation metric (AVFM), i.e., (1-ν norm ), till the arrival of initial 5000 connection requests. We also observed average adapted-α (A-alpha) and adapted-β (A-beta) components as individual fragmentation indicators as defined by relations in eq.…”

“…2). A few works with Markov Chain (MC) model tried to characterize the fragmentation in network by using a single channel and a super-channel services, [7], [8]. The blocking probability plot of individual services shows how the single channel requests rob off the resources from superchannel requests.…”