Danilo Bórquez-Paredes

The lack of standards in the performance evaluation of new resource allocation algorithms in multicore fiber elastic optical networks (MCF-EONs) compromises the fairness when comparing them with the state of the art. This paper reviews the different transmission parameters, network parameters, performance metrics, and baselines used by the recent proposals to build a framework for future benchmarking of such algorithms according to the nature of the network operation, whether static or dynamic. This framework aims to provide standards regarding evaluation criteria, scenarios, and performance metrics, as well as recommendations concerning technology advances to promote methodology and reproducibility in further related studies.

Flex Net Sim is a robust, high-performance, open-source C++ library designed to simulate resource allocation heuristics in elastic optical networks. Based on an event-driven simulation paradigm, the library has been purpose-built to address routing, modulation format, and spectrum allocation problems, as well as other related optimization challenges. With Flex Net Sim, researchers can focus solely on heuristic code development without requiring extensive programming expertise or complex configurations. Additionally, Flex Net Sim includes native tools for statistical analysis, including confidence interval estimation. To demonstrate its capabilities, a comprehensive benchmarking study was conducted using six allocation algorithms: first fit (FF); exact fit (EF); random fit (RF); best fit (BF); least loaded (LL); and proactive, fragmentation-aware spectrum management (PFA), across 105 real network topologies. The results indicate that LL consistently achieves the lowest blocking probability, while RF performs the worst in most scenarios. The library is fully extensible, actively maintained, and released under the MIT license, with source code available in a public repository.

TopoLib is an open-source Python library providing a curated collection of core network topologies and analytical traffic models for rapid network evaluation. The library includes 60 optical core networks sourced from operator websites, scientific literature, and research projects. Each topology contains node geo-locations, population figures, and per-node counts of data centers (DCs) and Internet exchange points (IXPs), along with link interconnections and distances. Three analytical traffic models are provided: two state-of-the-art models [gravitational and multi-period traffic (MPT)], and the proposed region aggregation model (RAM), which estimates traffic based on population, DCs, and IXPs. Applied to a topology, these models produce a traffic matrix suitable for network evaluation and cross-study comparison. All data can be exported for external use, and researchers may load their own topologies and modify model parameters to suit their specific needs. To demonstrate the library, three topologies are evaluated across nine distinct cases, covering three analyses: a comparison of traffic generated by each model, a sensitivity analysis of the RAM components, and a case study integrating TopoLib with MONET, a multi-period optical network planning tool based on Flex Net Sim [J. Opt. Commun. Netw.18, D16 (2026)10.1364/JOCN.586052], showcasing how the library can support exhaustive network utilization and infrastructure deployment studies.

Network virtualization is a key enabling technology for “Infrastructure as a Service” provisioning, increasing the flexibility and cost savings offered to customers. By extending the concept of server virtualization to the network infrastructure, the allocation of different, independent virtual networks over a single physical network is carried out on demand. A fundamental challenge in network virtualization systems is to choose which physical nodes and links to use for hosting virtual networks in the physical infrastructure, known as the “virtual network allocation” problem. All virtual network allocation proposals on elastic optical networks assume a centralized operation, deploying a single node with access to the network state global information and assigning resources accordingly. However, such configuration might exhibit the inherent problems of centralized systems: survivability and scalability. In this paper, we present a distributed protocol for resource discovery, mapping, and allocation of network virtualization systems. The distributed protocol is generic enough as to be used with different substrate networks. However, in this paper, it has been adapted to work over an elastic optical network infrastructure, where further considerations regarding the spectrum continuity and contiguity constraints must also be taken into account. The distributed protocol is based on the concept of alliances: upon the arrival of a virtual network request, agents located in the physical network nodes compete to form the first alliance able to host the virtual network. Because the first alliances to be formed are also the ones composed by nearby nodes, a good network resource usage is achieved. The feasibility of the distributed protocol was studied by evaluating its ability to successfully establish virtual networks within acceptable time and with low bandwidth consumption from the coordination messages.