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PILOT: A methodology for modeling the performance of packet connections

Authors :
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
Universitat Politècnica de Catalunya. GCO - Grup de Comunicacions Òptiques
Comellas Colomé, Jaume
Ruiz Ramírez, Marc
Velasco Esteban, Luis Domingo
Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
Universitat Politècnica de Catalunya. GCO - Grup de Comunicacions Òptiques
Comellas Colomé, Jaume
Ruiz Ramírez, Marc
Velasco Esteban, Luis Domingo
Publication Year :
2023

Abstract

Network Services automation requires predictable Quality of Service (QoS) performance, measured in terms of throughput, delay and jitter, to allow making proactive decisions. QoS is typically guaranteed by overprovisioning capacity dedicated to the packet connection, which increases costs for customers and network operators, especially when the traffic generated by the users and/or the virtual functions highly varies over the time. This paper presents the PILOT methodology for modeling the performance of packet connections during commissioning testing in terms of throughput, delay and jitter. PILOT runs in a sandbox domain and constructs a scenario where an efficient traffic flow simulation environment, based on the CURSA-SQ model, is used to generate large amounts of data for Machine Learning (ML) model training and validation. The simulation scenario is tuned using real measurements of the connection obtained from a set of active probes.<br />The research leading to these results has received funding from the Smart Networks and Services Joint Undertaking under the European Union's Horizon Europe research and innovation programme under Grant Agreement No. 101095890 (PREDICT6G), from the Spanish MINECO and the European Union though the NextGeneration UNICO5G TIMING (TSI-063000- 2021-145/148/149), and the AEI IBON (PID2020-114135RB-I00) projects and from ICREA.<br />Peer Reviewed<br />Postprint (author's final draft)

Details

Database :
OAIster
Notes :
4 p., application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1417305112
Document Type :
Electronic Resource