相关论文: Benchmarking the Open Science Data Federation serv…

Automating the theory-experiment cycle requires effective distributed workflows that utilize a computing continuum spanning lab instruments, edge sensors, computing resources at multiple facilities, data sets distributed across multiple…

We present best practices and tools for professionals who support computational and data intensive (CDI) research projects. The practices resulted from an initiative that brings together national projects and university teams that include…

The LHCb collaboration is one of the four major experiments at the Large Hadron Collider at CERN. Many petabytes of data are produced by the detectors and Monte-Carlo simulations. The LHCb Grid interware LHCbDIRAC is used to make data…

Managing Research Data, and making it available for use/reuse by others in line with the UKRI Concordat on Open Research Data and FAIR principles, is a major issue for research-intensive organisations. In this case study we outline an…

Using SDN to configure and control a multi-site network involves writing code that handles low-level details. We describe preliminary work on a framework that takes a network description and set of policies as input, and handles all the…

There is an emerging consensus in the scientific software community that progress in scientific research is dependent on the "quality and accessibility of software at all levels" (wssspe.researchcomputing.org.uk/). This progress depends on…

Background: Open innovation highlights the potential benefits of external collaboration and knowledge-sharing, often exemplified through Open Source Software (OSS). The public sector has thus far mainly focused on the sharing of Open…

In spite of the new opportunities brought about by the Open RAN, advances in ML-based network automation have been slow, mainly because of the unavailability of large-scale datasets and experimental testing infrastructure. This slows down…

Collaboration across institutional boundaries is widespread and increasing today. It depends on federations sharing data that often have governance rules or external regulations restricting their use. However, the handling of data…

Increasing concerns and regulations about data privacy and sparsity necessitate the study of privacy-preserving, decentralized learning methods for natural language processing (NLP) tasks. Federated learning (FL) provides promising…

Software Defined Networking (SDN) is an emerging network control paradigm focused on logical centralization and programmability. At the same time, distributed routing protocols, most notably OSPF and IS-IS, are still prevalent in IP…

HTCondor is a major workload management system used in distributed high throughput computing (dHTC) environments, e.g., the Open Science Grid. One of the distinguishing features of HTCondor is the native support for data movement, allowing…

The Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) is one of the largest data producers in the scientific world, with standard data products centrally produced, and then used by often competing teams within the…

Edge Federation is a new computing paradigm that seamlessly interconnects the resources of multiple edge service providers. A key challenge in such systems is the deployment of latency-critical and AI based resource-intensive applications…

This work poses a distributed multi-resource allocation scheme for minimizing the weighted sum of latency and energy consumption in the on-device distributed federated learning (FL) system. Each mobile device in the system engages the model…

The National Fusion Collaboratory (NFC) project was created to advance scientific understanding and innovation in magnetic fusion research by enabling more efficient use of existing experimental facilities through more effective integration…

Background: Distributed Research Networks (DRNs) offer significant opportunities for collaborative multi-site research and have significantly advanced healthcare research based on clinical observational data. However, generating…

This paper describes a prototype of extended XDB. XDB is an open-source and extensible database architecture developed by National Aeronautics and Space Administration (NASA) to provide integration of heterogeneous and distributed…

Federated Learning (FL) is an emerging domain in the broader context of artificial intelligence research. Methodologies pertaining to FL assume distributed model training, consisting of a collection of clients and a server, with the main…

Data has become a crucial resource in the digital economy, fostering initiatives for secure and sovereign data sharing frameworks such as Data Spaces. However, these distributed environments require fine-grained access control mechanisms…