Zobrazeno 1 - 10
of 163
pro vyhledávání: '"Roberto Proietti"'
Autor:
Hasan Awad, Fehmida Usmani, Emanuele Virgillito, Rudi Bratovich, Roberto Proietti, Stefano Straullu, Francesco Aquilino, Rosanna Pastorelli, Vittorio Curri
Publikováno v:
Sensors, Vol 24, Iss 10, p 3041 (2024)
We present the use of interconnected optical mesh networks for early earthquake detection and localization, exploiting the existing terrestrial fiber infrastructure. Employing a waveplate model, we integrate real ground displacement data from seven e
Externí odkaz:
https://doaj.org/article/0622285fa71041a1847f04aca750180d
Publikováno v:
Optical Fiber Communication Conference (OFC) 2023.
We present a MAke-bEfore-break StraTegy for Reconfiguration in Optical datacenters (MAESTRO). The simulation results show a reduction in packet loss by up to 98% compared to a baseline reconfiguration method.
Autor:
Emanuele Virgillito, Stefano Straullu, Rudi Bratovich, Fransisco M. Rodriguez, Hasan Awad, Andrea Castoldi, Roberto Proietti, Andrea D'Amico, Francesco Aquilino, Rosanna Pastorelli, Vittorio Curri
Optical networks for data transmission have become a pervasive infrastructure in the last years in order to cope with the increasing bandwidth request, thus there is a huge potential to be employed as a wide fiber optic sensing network. In the terres
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::688ac08bfab39c41be7a9ddce7575a92
https://hdl.handle.net/11583/2976141
https://hdl.handle.net/11583/2976141
Autor:
Mehmet Berkay On, Sandeep Kumar Singh, Gamze Gul, Gregory S. Kanter, Roberto Proietti, Prem Kumar, S. J. Ben Yoo
Publikováno v:
Optical Fiber Communication Conference (OFC) 2023.
We experimentally demonstrate quantum channel monitoring by wavelength-time multiplexing of classical wrapper bits with quantum payloads. Bit-error-rate measurements of 5 Gb/s classical bits infer the coincidence-to-accidental ratio of the quantum ch
Publikováno v:
IEEE Journal on Selected Areas in Communications. 39:2878-2889
Deep reinforcement learning (DRL) enables autonomic optical networking by allowing the network control and management systems to self-learn successful networking policies from operational experiences. This paper proposes a transfer learning approach
Autor:
Xiaoliang Chen, Luis Velasco, Che-Yu Liu, Marc Ruiz, S. J. Ben Yoo, Fatemehsadat Tabatabaeimehr, Roberto Proietti
Publikováno v:
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Universitat Politècnica de Catalunya (UPC)
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new
Publikováno v:
Optics Express. 31:16623
This paper reports the design, fabrication, and experimental demonstration of a monolithic silicon photonic (SiPh) 32×32 Thin-CLOS arrayed waveguide grating router (AWGR) for scalable SiPh all-to-all interconnection fabrics. The 32×32 Thin-CLOS mak
We run various distributed machine learning (DML) architectures in a hybrid optical/electrical DCN and an optical DCN based on Hyper-FleX-LION. Experimental results show that Hyper-FleX-LION gains faster DML acceleration and improves acceleration rat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2580ee6bf250f4f7eb8346292a238c8d
https://hdl.handle.net/11583/2973049
https://hdl.handle.net/11583/2973049
Photonic spiking neural networks (PSNNs) potentially offer exceptionally high throughput and energy efficiency compared to their electronic neuromorphic counterparts while maintaining their benefits in terms of event-driven computing capability. Whil
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ddbcf653b9a4acaf866a75f965b0bda
http://hdl.handle.net/11583/2972016
http://hdl.handle.net/11583/2972016
Autor:
Marjan Fariborz, Mahyar Samani, Pouya Fotouhi, Roberto Proietti, Il-Min Yi, Venkatesh Akella, Jason Lowe-Power, Samuel Palermo, S. J. Ben Yoo
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031073113
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::62c1a01e9aa2c3aab08767eca794262c
https://hdl.handle.net/11583/2972984
https://hdl.handle.net/11583/2972984