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The Virtual Research Environment is an analysis platform developed at CERN serving the needs of scientific communities involved in European Projects. Its scope is to facilitate the development of end-to-end physics workflows, providing…
Shift of the power system generation from the fossil to the variable renewable sources prompted the system operators to search for new sources of flexibility, that is, new reserve providers. With the introduction of electric vehicles, smart…
The term Data Space, understood as the secure exchange of data in distributed systems, ensuring openness, transparency, decentralization, sovereignty, and interoperability of information, has gained importance during the last years.…
The classification of the most used load balancing algorithms in distributed systems (including cloud technology, cluster systems, grid systems) is described. Comparative analysis of types of the load balancing algorithms is conducted in…
The current transition in the European energy sector towards climate neutrality requires detailed and reliable energy system modeling. The quality and relevance of the energy system modeling highly depend on the availability and quality of…
The freud Python package is a powerful library for analyzing simulation data. Written with modern simulation and data analysis workflows in mind, freud provides a Python interface to fast, parallelized C++ routines that run efficiently on…
Context: The globalisation of activities associated with software development and use has introduced many challenges in practice and for research. While the predominant approach to research in software engineering has followed a positivist…
We describe collaboration networks consisting of research projects funded by the European Union and the organizations involved in those projects. The networks are of substantial size and complexity, but are important to understand due to…
Distribution grid operation faces new challenges caused by a rising share of renewable energy sources and the introduction of additional types of loads to the grid. With the increasing adoption of distributed generation and emerging…
In many countries, the currently observable transformation of the power supply system from a centrally controlled system towards a complex "system of systems", comprising lots of autonomously interacting components, leads to a significant…
The availability of powerful microprocessors and high-speed networks as commodity components has enabled high performance computing on distributed systems (wide-area cluster computing). In this environment, as the resources are usually…
Monte Carlo simulations are one of the major tools in statistical physics, complex system science, and other fields, and an increasing number of these simulations is run on distributed systems like clusters or grids. This raises the issue…
Aims. Numerical test-particle simulations are a reliable and frequently used tool to test analytical transport theories and to predict mean-free paths. The comparison between solutions of the diffusion equation and the particle flux is used…
Recently, increasingly large amounts of data are generated from a variety of sources. Existing data processing technologies are not suitable to cope with the huge amounts of generated data. Yet, many research works focus on Big Data, a…
With their high parallelism and resource needs, many scientific applications benefit from cloud deployments. Today, scientific applications are executed on dedicated pools of VMs, resulting in resource fragmentation: users pay for…
Data-driven models analyze power grids under incomplete physical information, and their accuracy has been mostly validated empirically using certain training and testing datasets. This paper explores error bounds for data-driven models…
Programming systems incorporating aspects of functional programming, e.g., higher-order functions, are becoming increasingly popular for large-scale distributed programming. New frameworks such as Apache Spark leverage functional techniques…
The Globus Data Grid architecture provides a scalable infrastructure for the management of storage resources and data that are distributed across Grid environments. These services are designed to support a variety of scientific…
There is a growing need for massive computational resources for the analysis of new astronomical datasets. To tackle this problem, we present here our first steps towards marrying two new and emerging technologies; the Virtual Observatory…
Grid computing consists of the coordinated use of large sets of diverse, geographically distributed resources for high performance computation. Effective monitoring of these computing resources is extremely important to allow efficient use…