Routing and Regenerator Planning in a Carrier’s Core ROADM Network

Regenerator Allocation in Nonlinear Elastic Optical Networks With Random Data Rates

“…In this section, we present the simulation results for the proposed regenerator allocation heuristic and compare it with previous algorithms [1,2]. The continental US topology (CONUS) with 75 nodes and 99 bidirectional links is studied.…”

“…We evaluate the BP performances of the rankings computed by the proposed and RR methods, respectively. The second benchmark is the greedy constrained-routing regenerator location heuristic (greedy-CRLP) [2] that minimizes the number of RSs subject to the shortest distance routing constraint. The greedy-CRLP algorithm takes the TR value as input and outputs a set of RSs.…”

“…where Q t is the set of nodes on the route of t, Seg(t) is the set of all possible segments on the route of t, α is the unit regenerator cost [2], and src(t) and dst(t) are the source and destination of t, respectively. Based on the sets of promising RS allocations, we select the overall RS allocation that satisfies the RS number constraint and achieves the minimum BP by solving the following optimization problem…”

“…The advent of colorless directionless reconfigurable optical add/drop multiplexers can support dynamic operation and optimization of elastic optical networks (EONs) [1], where sparse regenerator sites can be deployed to enable fast provisioning of services [2]. To allocate regenerator sites (RSs) efficiently and guarantee the quality of transmission (QoTs), it is necessary to accurately estimate the physical layer impairments (PLIs) and the traffic conditions in the network, which are usually tackled by using transmission reach (TR) and static traffic predictions in previous studies [1,2]. Recently, the Gaussian noise (GN) model [4] has been proposed to describe the PLIs analytically.…”

Regenerator Site Predeployment in Nonlinear Dynamic Flexible-Grid Networks

“…The advent of colorless directionless reconfigurable optical add/drop multiplexers (CD-ROADMs) and software-defined optical networking can support dynamic control, management, and optimization of flexible-grid networks 1 , where sparse regenerator sites can be predeployed to enable fast provisioning of services and reconfigurations 2 . To allocate regenerator site (RS) conservatively and effectively, it is necessary to accurately estimate the physical layer impairments (PLIs).…”