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Roberto Proietti
Researcher at University of California, Davis
Publications - 206
Citations - 3700
Roberto Proietti is an academic researcher from University of California, Davis. The author has contributed to research in topics: Optical switch & Wavelength-division multiplexing. The author has an hindex of 29, co-authored 192 publications receiving 3052 citations. Previous affiliations of Roberto Proietti include Sant'Anna School of Advanced Studies & University of California.
Papers
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Proceedings ArticleDOI
DOS: a scalable optical switch for datacenters
TL;DR: The architecture and performance studies of Datacenter Optical Switch designed for scalable and high-throughput interconnections within a data center are discussed and it is shown that even with 2 to 4 wavelengths, the performance of DOS is significantly better than an electrical switch network based on state-of-the-art flattened butterfly topology.
Journal ArticleDOI
Survey of Photonic Switching Architectures and Technologies In Support Of Spatially and Spectrally Flexible Optical Networking {[}Invited]
Dan M. Marom,Paul D. Colbourne,Antonio D'Errico,Nicolas K. Fontaine,Yuichiro Ikuma,Roberto Proietti,Liangjia Zong,Jose Manuel Rivas-Moscoso,Ioannis Tomkos +8 more
TL;DR: This tutorial paper surveys the photonic switching hardware solutions in support of evolving optical networking solutions enabling capacity expansion based on the proposed approaches and presents the first cost comparisons, to the knowledge, of the different approaches in an effort to quantify such tradeoffs.
Journal ArticleDOI
LIONS: An AWGR-Based Low-Latency Optical Switch for High-Performance Computing and Data Centers
TL;DR: This paper proposes an all-optical negative acknowledgement (AO-NACK) architecture in order to remove the need for loopback buffers in LIONS, and its different loopback buffering schemes are compared with the performance of the flattened butterfly electrical switching network.
Journal ArticleDOI
DeepRMSA: A Deep Reinforcement Learning Framework for Routing, Modulation and Spectrum Assignment in Elastic Optical Networks
TL;DR: In this paper, a deep reinforcement learning framework for routing, modulation and spectrum assignment (RMSA) in elastic optical networks (EONs) is proposed, where deep neural networks (DNNs) are trained with experiences of dynamic lightpath provisioning.
Journal ArticleDOI
Regenerative and reconfigurable all-optical logic gates for ultra-fast applications
TL;DR: In this paper, all-optical ultra-fast and reconfigurable logic gates have been implemented exploiting simple and low-cost schemes based on nonlinear optical loop mirrors, and their regenerative properties have been demonstrated.