LHCOPN and LHCONE: Status and Future Evolution

Martelli, Edoardo; Stancu, S.

doi:10.1088/1742-6596/664/5/052025

Cited by 36 publications

(23 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We evaluate the performance of BoxOpt on the topology from LHC Open Network Environment (LHCONE), a global science network consisting of 62 institutes (Martelli and Stancu 2015). We randomly select a topology for each institute from the Topology Zoo (Knight et al 2011), and then assemble the connections and topologies from previous steps into a unified large network.…”

Section: Methodsmentioning

confidence: 99%

Optimizing in the Dark: Learning an Optimal Solution through a Simple Request Interface

Xiang

Aspnes

et al. 2019

AAAI

View full text Add to dashboard Cite

Network resource reservation systems are being developed and deployed, driven by the demand and substantial benefits of providing performance predictability for modern distributed applications. However, existing systems suffer limitations: They either are inefficient in finding the optimal resource reservation, or cause private information (e.g., from the network infrastructure) to be exposed (e.g., to the user). In this paper, we design BoxOpt, a novel system that leverages efficient oracle construction techniques in optimization and learning theory to automatically, and swiftly learn the optimal resource reservations without exchanging any private information between the network and the user. We implement a prototype of BoxOpt and demonstrate its efficiency and efficacy via extensive experiments using real network topology and trace. Results show that (1) BoxOpt has a 100% correctness ratio, and (2) for 95% of requests, BoxOpt learns the optimal resource reservation within 13 seconds.

show abstract

Section: Methodsmentioning

confidence: 99%

Optimizing in the Dark: Learning an Optimal Solution through a Simple Request Interface

Xiang

Aspnes

et al. 2019

AAAI

View full text Add to dashboard Cite

show abstract

“…In addition to this key infrastructure, Belle II can take advantage of a part of the high speed links provided by Large Hadron Collider Optical Private Network (LHCOPN) [8].…”

Section: Belle II Networkmentioning

confidence: 99%

“…This agreement also helps to simplify the site network configuration. As regards the layer 3 service, Belle II has joined the Large Hadron Collider Open Network Environment (LHCONE) [8] network which connects several sites in the collaboration including all RAW Data Centres and KEK, the latter connected at 40Gbps in the current setup.…”

Section: Belle II Networkmentioning

confidence: 99%

Network in Belle II

Pardi

2020

EPJ Web Conf.

View full text Add to dashboard Cite

Belle II has started the Phase 3 data taking with a fully equipped detector. The data flow at the maximum luminosity is expected to be 12PB of data/year and will be analysed by a cutting-edge computing infrastructure spread over 26 Countries. Several of the major computing centres for HEP in Europe, USA and Canada will store the second copy of RAW data. In this scenario, the international network infrastructure for research plays a key role in supporting and orchestrating all the activities of data analysis and replication. The large-scale network data challenge will also take advantage from LHCONE VRF service and the support of network experts of KEKCC, Belle II sites and NREN. The program of major upgrade in 2019 empowered the connection among Japan, Europe and USA over a 100Gb geographic ring. In this work, we summarize the network requirements needed to accomplish all the tasks provided by the Belle II computing model. We also highlight the status of the major network links that support and advance Belle II. Lastly, we present the results of the last Network Data Challenge campaign performed between KEK and the main RAW data centres with the additional usage of the Data Transfer Node service provided by GÉANT.

show abstract

“…The goal of the test was to overload the LHCOPN [14] links between CERN and SARA-NIKHEF with fake Rucio file transfers, and then use manual router loadbalancing to offload traffic from LHCOPN to LHCONE to increase the overall available bandwidth. We want to verify that the offload is effective and thus it is possible to use spare bandwidth when the primary links are congested.…”

Section: Increased Usage Of Tapes and Networkmentioning

confidence: 99%

Evolution of the open-source data management system Ru-cio for LHC Run-3 and beyond ATLAS

et al. 2019

View full text Add to dashboard Cite

Rucio, the distributed data management system of the ATLAS experiment already manages more than 400 Petabytes of physics data on the grid. Rucio was incrementally improved throughout LHC Run-2 and is currently being prepared for the HL-LHC era of the experiment. Next to these improvements the system is currently evolving into a full-scale generic data management system for application beyond ATLAS, or even beyond high-energy physics. This contribution focuses on the development roadmap of Rucio for LHC Run-3, such as event level data management, generic meta-data support and increased usage of networks and tapes. At the same time Rucio is evolving beyond the original ATLAS requirements. This includes additional authentication mechanisms, generic database compatibility, deployment and packaging of the software stack in containers, and a project paradigm shift to a full-scale open source project..

show abstract

LHCOPN and LHCONE: Status and Future Evolution

Cited by 36 publications

References 0 publications

Optimizing in the Dark: Learning an Optimal Solution through a Simple Request Interface

Optimizing in the Dark: Learning an Optimal Solution through a Simple Request Interface

Network in Belle II

Evolution of the open-source data management system Ru-cio for LHC Run-3 and beyond ATLAS

Contact Info

Product

Resources

About