10,361 research outputs found

    DIET : new developments and recent results

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    Among existing grid middleware approaches, one simple, powerful, and flexibleapproach consists of using servers available in different administrative domainsthrough the classic client-server or Remote Procedure Call (RPC) paradigm.Network Enabled Servers (NES) implement this model also called GridRPC.Clients submit computation requests to a scheduler whose goal is to find aserver available on the grid. The aim of this paper is to give an overview of anNES middleware developed in the GRAAL team called DIET and to describerecent developments. DIET (Distributed Interactive Engineering Toolbox) is ahierarchical set of components used for the development of applications basedon computational servers on the grid.Parmi les intergiciels de grilles existants, une approche simple, flexible et performante consiste a utiliser des serveurs disponibles dans des domaines administratifs différents à travers le paradigme classique de l’appel de procédure àdistance (RPC). Les environnements de ce type, connus sous le terme de Network Enabled Servers, implémentent ce modèle appelé GridRPC. Des clientssoumettent des requêtes de calcul à un ordonnanceur dont le but consiste àtrouver un serveur disponible sur la grille.Le but de cet article est de donner un tour d’horizon d’un intergiciel développédans le projet GRAAL appelé DIET 1. DIET (Distributed Interactive Engineering Toolbox) est un ensemble hiérarchique de composants utilisés pour ledéveloppement d’applications basées sur des serveurs de calcul sur la grille

    EU DataGRID testbed management and support at CERN

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    In this paper we report on the first two years of running the CERN testbed site for the EU DataGRID project. The site consists of about 120 dual-processor PCs distributed over several testbeds used for different purposes: software development, system integration, and application tests. Activities at the site included test productions of MonteCarlo data for LHC experiments, tutorials and demonstrations of GRID technologies, and support for individual users analysis. This paper focuses on node installation and configuration techniques, service management, user support in a gridified environment, and includes considerations on scalability and security issues and comparisons with "traditional" production systems, as seen from the administrator point of view.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 7 pages, LaTeX. PSN THCT00

    Overlay networks for smart grids

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    An eco-friendly hybrid urban computing network combining community-based wireless LAN access and wireless sensor networking

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    Computer-enhanced smart environments, distributed environmental monitoring, wireless communication, energy conservation and sustainable technologies, ubiquitous access to Internet-located data and services, user mobility and innovation as a tool for service differentiation are all significant contemporary research subjects and societal developments. This position paper presents the design of a hybrid municipal network infrastructure that, to a lesser or greater degree, incorporates aspects from each of these topics by integrating a community-based Wi-Fi access network with Wireless Sensor Network (WSN) functionality. The former component provides free wireless Internet connectivity by harvesting the Internet subscriptions of city inhabitants. To minimize session interruptions for mobile clients, this subsystem incorporates technology that achieves (near-)seamless handover between Wi-Fi access points. The WSN component on the other hand renders it feasible to sense physical properties and to realize the Internet of Things (IoT) paradigm. This in turn scaffolds the development of value-added end-user applications that are consumable through the community-powered access network. The WSN subsystem invests substantially in ecological considerations by means of a green distributed reasoning framework and sensor middleware that collaboratively aim to minimize the network's global energy consumption. Via the discussion of two illustrative applications that are currently being developed as part of a concrete smart city deployment, we offer a taste of the myriad of innovative digital services in an extensive spectrum of application domains that is unlocked by the proposed platform

    Fog Computing: A Taxonomy, Survey and Future Directions

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    In recent years, the number of Internet of Things (IoT) devices/sensors has increased to a great extent. To support the computational demand of real-time latency-sensitive applications of largely geo-distributed IoT devices/sensors, a new computing paradigm named "Fog computing" has been introduced. Generally, Fog computing resides closer to the IoT devices/sensors and extends the Cloud-based computing, storage and networking facilities. In this chapter, we comprehensively analyse the challenges in Fogs acting as an intermediate layer between IoT devices/ sensors and Cloud datacentres and review the current developments in this field. We present a taxonomy of Fog computing according to the identified challenges and its key features.We also map the existing works to the taxonomy in order to identify current research gaps in the area of Fog computing. Moreover, based on the observations, we propose future directions for research

    Use of A Network Enabled Server System for a Sparse Linear Algebra Grid Application

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    Solving systems of linear equations is one of the key operations in linear algebra. Many different algorithms are available in that purpose. These algorithms require a very accurate tuning to minimise runtime and memory consumption. The TLSE project provides, on one hand, a scenario-driven expert site to help users choose the right algorithm according to their problem and tune accurately this algorithm, and, on the other hand, a test-bed for experts in order to compare algorithms and define scenarios for the expert site. Both features require to run the available solvers a large number of times with many different values for the control parameters (and maybe with many different architectures). Currently, only the grid can provide enough computing power for this kind of application. The DIET middleware is the GRID backbone for TLSE. It manages the solver services and their scheduling in a scalable way.La résolution de systèmes linéaires creux est une opération clé en algèbre linéaire. Beaucoup d’algorithmes sont utilisés pour cela, qui dépendent de nombreux paramètres, afin d’offrir une robustesse, une performance et une consommation mémoire optimales. Le projet GRID-TLSE fournit d’une part, un site d’expertise basé sur l’utilisation de scénarios pour aider les utilisateurs à choisir l’algorithme qui convient le mieux à leur problème ainsi que les paramètres associés; et d’autre part, un environnement pour les experts du domaine leur permettant de comparer efficacement des algorithmes et de définir dynamiquement de nouveaux scénarios d’utilisation. Ces fonctionnalités nécessitent de pouvoir exécuter les logiciels de résolution disponibles un grand nombre de fois,avec beaucoup de valeurs différentes des paramètres de contrôle (et éventuellement sur plusieurs architectures de machines). Actuellement, seule la grille peut fournir la puissance de calcul pour ce type d’applications. L’intergiciel DIETest utilisé pour gérer la grille, les différents services, et leur ordonnancement efficace
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