activity
20182026
most citedAn Overview on Application of Machine Learning Techniques in Optical Networks

2 citations · 3 across the 8 of their papers we have counts for

collaborators

9 papers

cs.ET2026

When Less is More: Emerging Network-Wide Use Cases for Hollow-Core Fibers in Optical Networks [Invited]

Mëmëdhe Ibrahimi, Giovanni Simone Sticca, Angelo Ferrara +2

Hollow-Core Fiber (HCF) is emerging as a disruptive technology for next-generation optical networks, offering 30\% lower propagation latency than standard Single-Mode Fiber (SMF),…

cs.NI2026

Measurement-Device Placement in MDI-QKD Networks with Minimal Trusted Relays

Tianqu Luo, Ibrahim Arslantas, Sezin Ozturk +8

Measurement-Device-Independent Quantum Key Distribution (MDI-QKD) removes detector side-channel vulnerabilities by delegating measurements to an untrusted relay that, when shared b…

cs.NI2026

LLMs and Optical Networks: A Symbiotic Relationship

Mëmëdhe Ibrahimi, Qiaolun Zhang, Giovanni S. Sticca +3

This paper explores the emerging symbiosis between LLMs and optical networks. Massive LLMs require geo-distributed training, which demands advanced optical transport capabilities t…

quant-ph2026

Selective Placement of Hollow-Core Fibers for QKD and Classical Communication Coexistence

Giovanni Simone Sticca, Alessandro Gagliano, Memedhe Ibrahimi +3

We investigate the benefits of partially upgrading optical networks with hollow-core fibers for QKD-classical communication coexistence. Results show that upgrading 40% of links in…

cs.DC2025

Holoscope: Open and Lightweight Telescope & Honeypot Platform

Andrea Sordello, Marco Mellia, Idilio Drago +7

The complexity and scale of Internet attacks call for distributed, cooperative observatories capable of monitoring malicious traffic across diverse networks. Holoscope is an open,…

cs.NI2025★ 1 cited

Vertical Federated Learning for Failure-Cause Identification in Disaggregated Microwave Networks

Fatih Temiz, Memedhe Ibrahimi, Francesco Musumeci +2

Machine Learning (ML) has proven to be a promising solution to provide novel scalable and efficient fault management solutions in modern 5G-and-beyond communication networks. In th…

cs.NI2025

Multi-Failure Localization in High-Degree ROADM-based Optical Networks using Rules-Informed Neural Networks

Ruikun Wang, Qiaolun Zhang, Jiawei Zhang +7

To accommodate ever-growing traffic, network operators are actively deploying high-degree reconfigurable optical add/drop multiplexers (ROADMs) to build large-capacity optical netw…

cs.NI2024

Shared-Protected Backup Paths Assignment with Mode Group Division Multiplexing in Optical Networks

Jiaheng Xiong, Qiaolun Zhang, Ruikun Wang +3

We evaluate the resource efficiency of Mode Group Division Multiplexing (MGDM) with shared path protection (SPP) in optical networks. On our case studies, SPP with MGDM obtains sig…

cs.NI2018★ 2 cited

An Overview on Application of Machine Learning Techniques in Optical Networks

Francesco Musumeci, Cristina Rottondi, Avishek Nag +4

Today's telecommunication networks have become sources of enormous amounts of widely heterogeneous data. This information can be retrieved from network traffic traces, network alar…