Abstract
In this paper we explore in details the framework ElasticO++, which is a simulation framework for Elastic Optical Networks using OMNeT++. ElasticO++ is the first software available capable of working with spectrum defragmentation in dynamic network scenarios. The flexibility offered by the discussed tool allows both academia and industry to develop and evaluate new algorithms and techniques for Elastic Optical Networks. In this paper, we focus on ElasticO++ architecture, algorithms, and the features which we consider makes our framework unique. Additionally, we present a simulation case study and the newer features we are currently developing.
Highlights
In the past few years, Elastic Optical Networking (EON) emerged as the “ generation” core network technology [1]–[3], intended to surpass Wavelength-Division Multiplexing (WDM) weaknesses and limitations [4]–[6]
Fragmentation losses lead to inefficient resource utilization and overall network performance degradation, increasing blocking probabilities as the unused slots remain scattered over the links and not enough contiguous spectrum slots may be available for new requests to be established
Before starting the development of the proposed framework, we searched for simulation tools capable of allowing implementation and testing of new algorithms for elastic optical networks, focusing on allocation and defragmentation scenarios
Summary
Abstract—In this paper we explore in details the framework ElasticO++, which is a simulation framework for Elastic Optical Networks using OMNeT++. ElasticO++ is the first software available capable of working with spectrum defragmentation in dynamic network scenarios. The flexibility offered by the discussed tool allows both academia and industry to develop and evaluate new algorithms and techniques for Elastic Optical Networks. We focus on ElasticO++ architecture, algorithms, and the features which we consider makes our framework unique. We present a simulation case study and the newer features we are currently developing
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