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Open Government Data (OGD) initiatives aim to enhance public participation and collaboration by making government data accessible to diverse stakeholders, fostering social, environmental, and economic benefits through public value…
With the growing popularity of various mobile devices, user targeting has received a growing amount of attention, which aims at effectively and efficiently locating target users that are interested in specific services. Most pioneering…
The General Data Protection Regulation (GDPR) is considered as the benchmark in the European Union (EU) for privacy and data protection standards. Since before its entry into force in 2018, substantial research has been conducted in the…
Intending to support new emerging applications with latency requirements below what can be offered by the cloud data centers, the edge and fog computing paradigms have reared. In such systems, the real-time instant data is processed closer…
Research process automation -- the reliable, efficient, and reproducible execution of linked sets of actions on scientific instruments, computers, data stores, and other resources -- has emerged as an essential element of modern science. We…
This paper discusses the latest generation of the MONARC (MOdels of Networked Analysis at Regional Centers) simulation framework, as a design and modeling tool for large scale distributed systems applied to HEP experiments. The simulation…
Selecting optimal resources for submitting jobs on a computational Grid or accessing data from a data grid is one of the most important tasks of any Grid middleware. Most modern Grid software today satisfies this responsibility and gives a…
Grid computing has emerged as an effective means of facilitating the sharing of distributed heterogeneous resources, enabling collaboration in large scale environments. However, the nature of Grid systems, coupled with the overabundance and…
This paper investigates an edge computing system where requests are processed by a set of replicated edge servers. We investigate a class of applications where similar queries produce identical results. To reduce processing overhead on the…
Inserting renewable energy in the electric grid in a decentralized manneris a key challenge of the energy transition. However, at local scale, both production and demand display erratic behavior, which makes it delicate to match them. It is…
The energy sector is experiencing a paradigm shift with the swift adoption of distributed energy sources, renewables, electric vehicles, and an evolving consumer-utility relationship. This necessitates the strategic integration of advanced…
Enterprise knowledge graphs (EKGa) are a novel paradigm for consolidating and semantically integrating large numbers of heterogeneous data sources into a comprehensive dataspace. The main goal of an EKG is to provide a data layer that is…
Electric vehicles (EVs) are finally making their way onto the roads, but the challenges concerning long charging times and impact on congestion of the power distribution grid are still not resolved. Proposed solutions depend on heavy…
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…
As data-driven methods are becoming pervasive in a wide variety of disciplines, there is an urgent need to develop scalable and sustainable tools to simplify the process of data science, to make it easier to keep track of the analyses being…
This paper examines how a "Distributed Heterogeneous Relational Data Warehouse" can be integrated in a Grid environment that will provide physicists with efficient access to large and small object collections drawn from databases at…
This paper shows an analysis of the gridded European precipitation data. We combine simple linear regression with data mining tools like clustering, and evaluate the strength of the results by the modern bootstrap methods. We have used the…
Grid computing is a distributed computing paradigm which aims to aggregate several heterogeneous and distributed resources, belonging to different and independent organizations, in a dynamic, transparent and coordinated way. Since its…
The Grid and Cloud User Support Environment (gUSE) enables users convenient and easy access to grid and cloud infrastructures by providing a general purpose, workflow-oriented graphical user interface to create and run workflows on various…
The transition to renewable energy sources for data centers has become a popular trend in the IT industry. However, the volatility of renewable energy, such as solar and wind power, impedes the operation of green data centers. In this work,…