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Behnam Shariati

Publications and source records attributed to Behnam Shariati.

6 recordsLinked to original sources
arXiv2026

Optical Network Digital Twin: From Digital Coherent Transmission to Intelligent Network Operations

Optical Network Digital Twins (ONDTs) are emerging as a key framework for representing, synchronizing, and utilizing the physical state of optical networks for quality-of-transmission (QoT) estimation, optimization, and intelligent operation. This survey provides a comprehensive view of ONDTs, spanning digital coherent transmission and physical-layer observability to intelligent network operations. We systematically organize ONDT technologies from ecosystem, functional, control, and implementation architecture perspectives and review the enabling technologies required to construct, synchronize, and utilize digital representations of physical optical networks. As a unifying framework to describe both ONDT design and validation, we introduce a categorization based on the following figures of merit: Fidelity, Dynamicity, and Deployability (FDD). In particular, we emphasize fit-for-purpose Fidelity, where modeling effort focuses on the physical effects of components rather than solely maximizing model accuracy, favoring scalability and generalizability. Furthermore, experimental and field validations are examined to evaluate the practical applicability of ONDT technologies. We further examine experimental and field validations, from physics-based QoT estimation and measurement-informed model refinement to field synchronization, service provisioning, multi-domain observability, and infrastructure characterization. Finally, we discuss the complementary roles of ONDTs and AI agents toward autonomous optical networks and identify key research directions for practical deployment.

eess.SY↗
arXiv2025

HAL 9000: a Risk Manager for ITSs

HAL 9000 is an Intrusion Tolerant Systems (ITSs) Risk Manager, which assesses configuration risks against potential intrusions. It utilizes gathered threat knowledge and remains operational, even in the absence of updated information. Based on its advice, the ITSs can dynamically and proactively adapt to recent threats to minimize and mitigate future intrusions from malicious adversaries. Our goal is to reduce the risk linked to the exploitation of recently uncovered vulnerabilities that have not been classified and/or do not have a script to reproduce the exploit, considering the potential that they may have already been exploited as zero-day exploits. Our experiments demonstrate that the proposed solution can effectively learn and replicate National Vulnerability Database's evaluation process with 99% accuracy.

cs.CR↗
arXiv2023

Launch Power Optimization for Dynamic Elastic Optical Networks over C+L Bands

We propose an algorithm for calculating the optimum launch power over the entire C+L bands by maximizing the cumulative link GSNR of a channel plan built upon multiple modulation formats, with application to dynamic EONs. Exact last-fit spectrum assignment proves to outperform exact first-fit in terms of average GSNR at arrival time.

eess.SP↗
arXiv2020

Privacy-Preserving Distributed Learning Framework for 6G Telecom Ecosystems

We present a privacy-preserving distributed learning framework for telecom ecosystems in the 6G-era that enables the vision of shared ownership and governance of ML models, while protecting the privacy of the data owners. We demonstrate its benefits by applying it to the use-case of Quality of Transmission (QoT) estimation in multi-domain multi-vendor optical networks, where no data of individual domains is shared with the network management system (NMS).

cs.NI↗