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Dissertations / Theses on the topic 'Scheduling, data management, grid computing'

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1

Agarwalla, Bikash Kumar. "Resource management for data streaming applications." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/34836.

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This dissertation investigates novel middleware mechanisms for building streaming applications. Developing streaming applications is a challenging task because (i) they are continuous in nature; (ii) they require fusion of data coming from multiple sources to derive higher level information; (iii) they require
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2

Vernois, Antoine. "Ordonnancement et réplication de données bioinformatiques dans un contexte de grille de calcul." Lyon, École normale supérieure (sciences), 2006. http://www.theses.fr/2006ENSL0368.

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Au cours de cette thèse, nous nous sommes placés dans le contexte bien > particulier d'une catégorie d'applications bioinformatiques dont les > caractéristiques sont d'utiliser des banques de données de références en > lecture seule et d'avoir un coût en temps de calcul affine en la taille des > données. Une autre caractéristique concernant l'utilisation de ces > applications est que leur schéma d'utilisation reste constant dans le > temps. Dans ce cadre, nous avons défini un algorithme basé sur un programme > linéaire permettant de calculer un ordonnancement et un placeme
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3

Tordsson, Johan. "Portable Tools for Interoperable Grids : Modular Architectures and Software for Job and Workflow Management." Doctoral thesis, Umeå universitet, Institutionen för datavetenskap, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-19630.

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The emergence of Grid computing infrastructures enables researchers to shareresources and collaborate in more efficient ways than before, despite belongingto different organizations and being geographically distributed. While the Gridcomputing paradigm offers new opportunities, it also gives rise to newdifficulties. This thesis investigates methods, architectures, and algorithmsfor a range of topics in the area of Grid resource management. One studiedtopic is how to automate and improve resource selection, despite heterogeneityin Grid hardware, software, availability, ownership, and usage poli
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4

Smith, Andrew Cameron. "LHCb data management on the computing grid." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/3018.

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The LHCb detector is one of the four experiments being built to harness the proton-proton collisions provided by the Large Hadron Collider (LHC) at the European Organisation for Nuclear Research (CERN). The data rate expected, when the LHC experiments are fully operational, eclipses that of any previous scientific experiments and has motivated the adoption of a grid computing paradigm to store and process the data. Managing PetaBytes of data in a distributed environment provides a rich set of challenges related to scalability, reliability and performance. This thesis will present the data mana
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5

Buyya, Rajkumar 1970. "Economic-based distributed resource management and scheduling for grid computing." Monash University, School of Computer Science and Software Engineering, 2002. http://arrow.monash.edu.au/hdl/1959.1/8760.

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6

Bsoul, Mohammad. "Economic scheduling in Grid computing using Tender models." Thesis, Loughborough University, 2007. https://dspace.lboro.ac.uk/2134/3094.

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Economic scheduling needs to be considered for Grid computing environment, because it gives an incentive for resource providers to supply their resources. Moreover, it enforces efficient use of resources, because the users have to pay for their use. Tendering is a suitable model for Grid scheduling because users start the negotiations for finding suitable resources for executing their jobs. Furthermore, the users specify their job requirements with their requests and therefore the resources reply with bids that are based on the cost of taking on the job and the availability of their processors
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7

Delgado, Javier. "A grid computing network platform for enhanced data management and visualization." FIU Digital Commons, 2007. http://digitalcommons.fiu.edu/etd/2766.

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This thesis presents a novel approach towards providing a collaboration environment by using Grid Computing. The implementation includes the deployment of a cluster attached to a mural display for high performance computing and visualization and a Grid-infrastructure for sharing storage space across a wide area network and easing the remote use of the computing resources. A medical data processing application is implemented on the platform. The outcome is enhanced use of remote storage facilities and quick return time for computationally-intensive problems. The central issue of this thesis wor
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8

Brodard, Zacharie. "Workflow management and scheduling in a cloud computing context." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-249714.

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Public cloud providers have had a tremendous impact on the software engineering world recently by offering on-demand computing infrastructures and scalable managed solutions. The goal of this master degree project is to determine whether these services offered by public cloud providers can improve the design of workflow management and scheduling systems for data-driven workflows. A cloud based architecture for a distributed workflow management system was designed, implemented and experimented on. It allowed to confirm the value of cloud computing solutions to solve workflow scheduling problems
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9

Espling, Daniel. "Enabling Technologies for Management of Distributed Computing Infrastructures." Doctoral thesis, Umeå universitet, Institutionen för datavetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-80129.

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Computing infrastructures offer remote access to computing power that can be employed, e.g., to solve complex mathematical problems or to host computational services that need to be online and accessible at all times. From the perspective of the infrastructure provider, large amounts of distributed and often heterogeneous computer resources need to be united into a coherent platform that is then made accessible to and usable by potential users. Grid computing and cloud computing are two paradigms that can be used to form such unified computational infrastructures. Resources from several indepe
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10

Radwan, Ahmed M. "Information Integration in a Grid Environment Applications in the Bioinformatics Domain." Scholarly Repository, 2010. http://scholarlyrepository.miami.edu/oa_dissertations/509.

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Grid computing emerged as a framework for supporting complex operations over large datasets; it enables the harnessing of large numbers of processors working in parallel to solve computing problems that typically spread across various domains. We focus on the problems of data management in a grid/cloud environment. The broader context of designing a services oriented architecture (SOA) for information integration is studied, identifying the main components for realizing this architecture. The BioFederator is a web services-based data federation architecture for bioinformatics applications. Bas
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11

Akimana, Rachel. "Grid Fault management techniques: the case of a Grid environment with malicious entities." Doctoral thesis, Universite Libre de Bruxelles, 2008. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210460.

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<p>La tolérance et la gestion des fautes dans les grilles de données/calcul est d’une importance capitale. En effet, comme dans tout autre système distribué, les composants d’une grille sont susceptibles de tomber en panne à tout moment. Mais le risque de panne croît avec la taille du système, et est donc plus exacerbé dans un système de grille. En plus, tout en essayant de mettre à profit les ressources offertes par la grille, les applications tournant sur celle-ci sont de plus en plus complexes (ex. impliquent des interactions complexes, prennent des jours d’exécution), ce qui les rend plus
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12

Espling, Daniel. "Metadata Management in Multi-Grids and Multi-Clouds." Licentiate thesis, Umeå universitet, Institutionen för datavetenskap, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-51159.

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Grid computing and cloud computing are two related paradigms used to access and use vast amounts of computational resources. The resources are often owned and managed by a third party, relieving the users from the costs and burdens of acquiring and managing a considerably large infrastructure themselves. Commonly, the resources are either contributed by different stakeholders participating in shared projects (grids), or owned and managed by a single entity and made available to its users with charging based on actual resource consumption (clouds). Individual grid or cloud sites can form collab
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13

Tang, Jia. "An agent-based peer-to-peer grid computing architecture." Access electronically, 2005. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20060508.151716/index.html.

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14

De, Luca Silvia. "Studies of CMS data access patterns with machine learning techniques." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/12021/.

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This thesis presents a study of the Grid data access patterns in distributed analysis in the CMS experiment at the LHC accelerator. This study ranges from the deep analysis of the historical patterns of access to the most relevant data types in CMS, to the exploitation of a supervised Machine Learning classification system to set-up a machinery able to eventually predict future data access patterns - i.e. the so-called dataset “popularity” of the CMS datasets on the Grid - with focus on specific data types. All the CMS workflows run on the Worldwide LHC Computing Grid (WCG) computing cente
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15

Al-Shishtawy, Ahmad. "Self-Management for Large-Scale Distributed Systems." Doctoral thesis, KTH, Programvaruteknik och Datorsystem, SCS, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-101661.

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Autonomic computing aims at making computing systems self-managing by using autonomic managers in order to reduce obstacles caused by management complexity. This thesis presents results of research on self-management for large-scale distributed systems. This research was motivated by the increasing complexity of computing systems and their management. In the first part, we present our platform, called Niche, for programming self-managing component-based distributed applications. In our work on Niche, we have faced and addressed the following four challenges in achieving self-management in a dy
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16

Ayoubi, Tarek. "Distributed Data Management Supporting Healthcare Workflow from Patients’ Point of View." Thesis, Blekinge Tekniska Högskola, Avdelningen för för interaktion och systemdesign, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-6030.

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Patient’s mobility throughout his lifetime leaves a trial of information scattered in laboratories, clinical institutes, primary care units, and other hospitals. Hence, the medical history of a patient is valuable when subjected to special healthcare units or undergoes home-care/personal-care in elderly stage cases. Despite the rhetoric about patient-centred care, few attempts were made to measure and improve in this arena. In this thesis, we will describe and implement a high-level view of a Patient Centric information management, deploying at a preliminary stage, the use of Agent Technologie
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17

Doraimani, Shyamala. "Filecules : a new granularity for resource management in grids." [Tampa, Fla] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0001905.

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18

Netti, Alessio. "Development of Data-Driven Dispatching Heuristics for Heterogeneous HPC Systems." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/14541/.

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Nell’ambito dei sistemi High-Performance Computing, l'uso di euristiche di dispatching efficaci, per lo scheduling e l'allocazione dei jobs in arrivo, è fondamentale al fine di ottenere buoni livelli di Quality of Service. In questo elaborato ci concentreremo sul design e l’analisi di euristiche di allocazione delle risorse, che saranno progettate per sistemi HPC eterogenei, nei quali i nodi possono essere equipaggiati con diverse tipologie di unità di elaborazione. Impiegheremo poi euristiche data-driven per la predizione della durata dei jobs, e valuteremo il tutto dal punto di vista del thr
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19

Moise, Diana Maria. "Optimizing data management for MapReduce applications on large-scale distributed infrastructures." Thesis, Cachan, Ecole normale supérieure, 2011. http://www.theses.fr/2011DENS0067/document.

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Les applications data-intensive sont largement utilisées au sein de domaines diverses dans le but d'extraire et de traiter des informations, de concevoir des systèmes complexes, d'effectuer des simulations de modèles réels, etc. Ces applications posent des défis complexes tant en termes de stockage que de calcul. Dans le contexte des applications data-intensive, nous nous concentrons sur le paradigme MapReduce et ses mises en oeuvre. Introduite par Google, l'abstraction MapReduce a révolutionné la communauté intensif de données et s'est rapidement étendue à diverses domaines de recherche et de
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20

Kurt, Mehmet Can. "Fault-tolerant Programming Models and Computing Frameworks." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1437390499.

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21

Gomes, Diego da Silva. "JavaRMS : um sistema de gerência de dados para grades baseado num modelo par-a-par." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2008. http://hdl.handle.net/10183/15533.

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A grande demanda por computação de alto desempenho culminou na construção de ambientes de execução de larga escala como as Grades Computacionais. Não diferente de outras plataformas de execução, seus usuários precisam obter os dados de entrada para suas aplicações e muitas vezes precisam armazenar os resultados por elas gerados. Apesar de o termo Grade ter surgido de uma metáfora onde os recursos computacionais estão tão facilmente acessíveis como os da rede elétrica, as ferramentas para gerenciamento de dados e de recursos de armazenamento disponíveis estão muito aquém do necessário para conc
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22

Cai, Zhongtang. "Risk-based proactive availability management." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/22581.

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Thesis (Ph. D.)--Computing, Georgia Institute of Technology, 2008.<br>Committee Member: Ahamad, Mustaque; Committee Member: Eisenhauer, Greg; Committee Member: Milojicic, Dejan; Committee Member: Pu, Calton; Committee Member: Schwan, Karsten.
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23

Gkikas, Nikolaos. "Data Transfer and Management through the IKAROS framework : Adopting an asynchronous non-blocking event driven approach to implement the Elastic-Transfer's IMAP client-server connection." Thesis, KTH, Radio Systems Laboratory (RS Lab), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166740.

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Given the current state of input/output (I/O) and storage devices in petascale systems, incremental solutions would be ineffective when implemented in exascale environments. According to the "The International Exascale Software Roadmap", by Dongarra, et al. existing I/O architectures are not sufficiently scalable, especially because current shared file systems have limitations when used in large-scale environments. These limitations are: Bandwidth does not scale economically to large-scale systems, I/O traffic on the high speed network can impact on and be influenced by other unrelated jobs, a
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24

Rios, Ricardo Araújo. "SLOT: uma ferramenta dinâmica para escalonamento global de aplicações em grades computacionais." Universidade Federal de São Carlos, 2008. https://repositorio.ufscar.br/handle/ufscar/401.

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Made available in DSpace on 2016-06-02T19:05:34Z (GMT). No. of bitstreams: 1 2082.pdf: 3574461 bytes, checksum: e92a97c5bb512846ce12d22f63592a23 (MD5) Previous issue date: 2008-05-19<br>Financiadora de Estudos e Projetos<br>The constant improvement in performance that computers and interconnection networks present has favored the use of distributed computational resources, and given rise to Grid Computing. This new approach uses heterogeneous and geographically distributed resources to resolve problems with high computational costs. The execution of applications in this environment is genera
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25

Raffa, Viviana. "Edge/cloud virtualization techniques and resources allocation algorithms for IoT-based smart energy applications." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/22864/.

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Nowadays, the installation of residential battery energy storage (BES) has increased as a consequence of the decrease in the cost of batteries. The coupling of small-scale energy generation (residential PV) and residential BES promotes the integration of microgrids (MG), i.e., clusters of local energy sources, energy storages, and customers which are represented as a single controllable entity. The operations between multiple grid-connected MGs and the distribution network can be coordinated by controlling the power exchange; however, in order to achieve this level of coordination, a co
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26

Caballé, Llobet Santi. "A Computational Model for the Construction of Knowledge-based Collaborative Learning Distributed Applications." Doctoral thesis, Universitat Oberta de Catalunya, 2008. http://hdl.handle.net/10803/9127.

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en català:<br/><br/>Un camp de recerca important dins del paradigma del Computer-Supported Collaborative Learning (CSCL) és la importància en la gestió eficaç de la informació d'esdeveniments generada durant l'activitat de l'aprenentatge col·laboratiu virtual, per a proporcionar coneixement sobre el comportament dels membres del grup. Aquesta visió és especialment pertinent en l'escenari educatiu actual que passa d'un paradigma tradicional - centrat en la figura d'un instructor magistral - a un paradigma emergent que considera els estudiants com actors centrals en el seu procés d'aprenentatge.
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