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The MonALISA (Monitoring Agents in A Large Integrated Services Architecture) system provides a distributed monitoring service. MonALISA is based on a scalable Dynamic Distributed Services Architecture which is designed to meet the needs of physics collaborations for monitoring global Grid s ystems, and is implemented using JINI/JAVA and WSDL/SOAP(More)
In this paper we present the Experiment Dashboard monitoring system, which is currently in use by four Large Hadron Collider (LHC)[1] experiments. The goal of the Experiment Dashboard is to monitor the activities of the LHC experiments on the distributed infrastructure, providing monitoring data from the virtual organization (VO) and user perspectives. The(More)
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 of Grid architectures has a vital importance in the future deployment of Grid systems for providing the users an(More)
Grid computing has gained an increasing importance in the last years, especially in the academic environments, offering the possibility to rapidly solve complex scientific problems. The monitoring of the Grid jobs has a vital importance for analyzing the system's performance, for providing the users an appropriate feedback , and for obtaining historical(More)
The successful administration of a global Data Grid system requires collecting and storing relevant monitoring information, using it to show the status and the trends of the entire system. The collected information is further used in developing the higher-level services and components of the distributed system to provide a degree of automated operational(More)
Quantum thermodynamics is a research field that aims at fleshing out the ultimate limits of thermodynamic processes in the deep quantum regime. A complete picture of quantum thermodynamics allows for catalysts, i.e., systems facilitating state transformations while remaining essentially intact in their state, very much reminding of catalysts in chemical(More)
In this work we argue that when dealing with data-intensive applications in large distributed systems it is important to go beyond the simple scheduling of application tasks that have to run, and to support at the framework level the process of dynamically changing the configuration of the underlying resources, based on actual requirements, in a coherent(More)
Handling high-performance data transfers is a hot topic today, in the context of the numerous data-intensive applications which begin to be used not only in local clusters, but also in large distributed systems. For this purpose, we have developed a framework based on MONALISA that allows intelligent handling of data transfers in large environments, both(More)
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