Related papers: A lightweight analysis farm for fundamental physic…
Dynaswap project reports on developing a coherently integrated and trustworthy holistic secure workflow protection architecture for cyberinfrastructures which can be used on virtual machines deployed through cyberinfrastructure (CI)…
Cloud Computing holds the potential to eliminate the requirements for setting up of high-cost computing infrastructure for the IT-based solutions and services that the industry uses. It promises to provide a flexible IT architecture,…
With the ever-increasing range of applications of Internet in Things (IoT) and sensor networks, challenges are emerging in various categories of classification tasks. Applications such as vehicular networking, UAV swarm coordination and…
Scientific computing applications usually need huge amounts of computational power. The cloud provides interesting high-performance computing solutions, with its promise of virtually infinite resources on demand. However, migrating…
Large High Energy Physics (HEP) experiments adopted a distributed computing model more than a decade ago. WLCG, the global computing infrastructure for LHC, in partnership with the US Open Science Grid, has achieved data management at the…
Edge computing addresses critical limitations of cloud computing such as high latency and network congestion by decentralizing processing from cloud to the edge. However, the need for software replication across heterogeneous edge devices…
The operation of instruments and detectors in laboratory or beamline environments presents a complex challenge, requiring stable operation of multiple concurrent devices, often controlled by separate hardware and software solutions. These…
With weather becoming more extreme both in terms of longer dry periods and more severe rain events, municipal water networks are increasingly under pressure. The effects include damages to the pipes, flash floods on the streets and combined…
Due to the complexity of robotics, the reproducibility of results and experiments is one of the fundamental problems in robotics research. While the problem has been identified by the community, the approaches that address the problem…
The distributed inference paradigm enables the computation workload to be distributed across multiple devices, facilitating the implementations of deep learning based intelligent services on extremely resource-constrained Internet of Things…
As Deep Neural Networks (DNNs) have become an increasingly ubiquitous workload, the range of libraries and tooling available to aid in their development and deployment has grown significantly. Scalable, production quality tools are freely…
Federated testbeds enable collaborative research by providing access to diverse resources, including computing power, storage, and specialized hardware like GPUs, programmable switches and smart Network Interface Cards (NICs). Efficiently…
Scientific workflows are a cornerstone of modern scientific computing. They are used to describe complex computational applications that require efficient and robust management of large volumes of data, which are typically stored/processed…
In every form of digital store-and-forward communication, intermediate forwarding nodes are computers, with attendant memory and processing resources. This has inevitably stimulated efforts to create a wide-area infrastructure that goes…
Monitoring the technical condition of infrastructure is a crucial element to its maintenance. Currently applied methods are outdated, labour-intensive and inaccurate. At the same time, the latest methods using Artificial Intelligence…
New testing and development procedures and methods are needed to address topics like power system stability, operation and control in the context of grid integration of rapidly developing smart grid technologies. In this context, individual…
Often corporations need tools to improve their decision making in a competitive market. In general, these tools are based on data warehouse platforms to mange and analyze large amounts of data. However, several of these corporations do not…
Dalek is an experimental compute cluster designed to evaluate the performance of heterogeneous, consumer-grade hardware for software design, prototyping, and algorithm development. In contrast to traditional computing centers that rely on…
Collaborative Intrusion Detection Systems (CIDS) are increasingly adopted to counter cyberattacks, as their collaborative nature enables them to adapt to diverse scenarios across heterogeneous environments. As distributed critical…
The increasing penetration of inverter-based resources (IBRs) is fundamentally reshaping power system dynamics and creating new challenges for stability assessment. Data-driven approaches, and in particular machine learning models, require…