output
20202023
most citedSoftware-Defined Network for End-to-end Networked Science at the Exascale

25 citations

8 papers

cs.NI2023★ 5 cited

Effectiveness and predictability of in-network storage cache for scientific workflows

Caitlin Sim, Kesheng Wu, Alex Sim +6

Large scientific collaborations often have multiple scientists accessing the same set of files while doing different analyses, which create repeated accesses to the large amounts o…

cs.NI2023★ 6 cited

Analyzing Transatlantic Network Traffic over Scientific Data Caches

Z. Deng, A. Sim, K. Wu +6

Large scientific collaborations often share huge volumes of data around the world. Consequently a significant amount of network bandwidth is needed for data replication and data ac…

cs.NI2022★ 5 cited

Managed Network Services for Exascale Data Movement Across Large Global Scientific Collaborations

Frank Würthwein, Jonathan Guiang, Aashay Arora +10

Unique scientific instruments designed and operated by large global collaborations are expected to produce Exabyte-scale data volumes per year by 2030. These collaborations depend…

cs.DC2022★ 2 cited

Studying Scientific Data Lifecycle in On-demand Distributed Storage Caches

Julian Bellavita, Alex Sim, Kesheng Wu +4

The XRootD system is used to transfer, store, and cache large datasets from high-energy physics (HEP). In this study we focus on its capability as distributed on-demand storage cac…

cs.NI2022★ 4 cited

Access Trends of In-network Cache for Scientific Data

Ruize Han, Alex Sim, Kesheng Wu +6

Scientific collaborations are increasingly relying on large volumes of data for their work and many of them employ tiered systems to replicate the data to their worldwide user comm…

cs.NI2021★ 6 cited

Analyzing scientific data sharing patterns for in-network data caching

Elizabeth Copps, Huiyi Zhang, Alex Sim +6

The volume of data moving through a network increases with new scientific experiments and simulations. Network bandwidth requirements also increase proportionally to deliver data w…