Littérature scientifique sur le sujet « Large-scale infrastructures »
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Articles de revues sur le sujet "Large-scale infrastructures"
Lui, P. C., et T. S. Tan. « Building Integrated Large-Scale Urban Infrastructures : Singapore's Experience ». Journal of Urban Technology 8, no 1 (avril 2001) : 49–68. http://dx.doi.org/10.1080/10630730120052172.
Texte intégralMarian, BABIK, FEDORKO Ivan, HOOK Nicholas, LANSDALE Thomas Hector, LENKES Daniel, SIKET Miroslav et WALDRON Denis. « LEMON - LHC Era Monitoring for Large-Scale Infrastructures ». Journal of Physics : Conference Series 331, no 5 (23 décembre 2011) : 052025. http://dx.doi.org/10.1088/1742-6596/331/5/052025.
Texte intégralFilelis-Papadopoulos, Christos K., George A. Gravvanis et Panagiotis E. Kyziropoulos. « A framework for simulating large scale cloud infrastructures ». Future Generation Computer Systems 79 (février 2018) : 703–14. http://dx.doi.org/10.1016/j.future.2017.06.017.
Texte intégralRammelt, Crelis. « Infrastructures as Catalysts : Precipitating Uneven Patterns of Development from Large-Scale Infrastructure Investments ». Sustainability 10, no 4 (22 avril 2018) : 1286. http://dx.doi.org/10.3390/su10041286.
Texte intégralLan, Cheng Ming, et Wen Feng Liu. « Structural Health Monitoring Cloud and its Applications for Large-Scale Infrastructures ». Applied Mechanics and Materials 330 (juin 2013) : 418–25. http://dx.doi.org/10.4028/www.scientific.net/amm.330.418.
Texte intégralGehl, Robert, et Fenwick McKelvey. « Bugging out : darknets as parasites of large-scale media objects ». Media, Culture & ; Society 41, no 2 (20 décembre 2018) : 219–35. http://dx.doi.org/10.1177/0163443718818379.
Texte intégralBabik, Marian, Ivan Fedorko et David Rodrigues. « Cluman : Advanced cluster management for the large-scale infrastructures ». Journal of Physics : Conference Series 331, no 5 (23 décembre 2011) : 052002. http://dx.doi.org/10.1088/1742-6596/331/5/052002.
Texte intégralTan, Yongmin, Vinay Venkatesh et Xiaohui Gu. « Resilient Self-Compressive Monitoring for Large-Scale Hosting Infrastructures ». IEEE Transactions on Parallel and Distributed Systems 24, no 3 (mars 2013) : 576–86. http://dx.doi.org/10.1109/tpds.2012.167.
Texte intégralNicolae, Bogdan, Gabriel Antoniu, Luc Bougé, Diana Moise et Alexandra Carpen-Amarie. « BlobSeer : Next-generation data management for large scale infrastructures ». Journal of Parallel and Distributed Computing 71, no 2 (février 2011) : 169–84. http://dx.doi.org/10.1016/j.jpdc.2010.08.004.
Texte intégralDutta, Kaushik, Debra VanderMeer et Krithi Ramamritham. « Managing RFID events in large-scale distributed RFID infrastructures ». Information Technology and Management 12, no 3 (3 février 2011) : 253–72. http://dx.doi.org/10.1007/s10799-011-0085-6.
Texte intégralThèses sur le sujet "Large-scale infrastructures"
Capizzi, Sirio <1980>. « A tuple space implementation for large-scale infrastructures ». Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2008. http://amsdottorato.unibo.it/914/1/Tesi_Capizzi_Sirio.pdf.
Texte intégralCapizzi, Sirio <1980>. « A tuple space implementation for large-scale infrastructures ». Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2008. http://amsdottorato.unibo.it/914/.
Texte intégralGattoni, Gaia. « Analysis of the infrastructures to build immersive visit at large scale ». Master's thesis, Alma Mater Studiorum - Università di Bologna, 2022.
Trouver le texte intégralMoise, 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.
Texte intégralData-intensive applications are nowadays, widely used in various domains to extract and process information, to design complex systems, to perform simulations of real models, etc. These applications exhibit challenging requirements in terms of both storage and computation. Specialized abstractions like Google’s MapReduce were developed to efficiently manage the workloads of data-intensive applications. The MapReduce abstraction has revolutionized the data-intensive community and has rapidly spread to various research and production areas. An open-source implementation of Google's abstraction was provided by Yahoo! through the Hadoop project. This framework is considered the reference MapReduce implementation and is currently heavily used for various purposes and on several infrastructures. To achieve high-performance MapReduce processing, we propose a concurrency-optimized file system for MapReduce Frameworks. As a starting point, we rely on BlobSeer, a framework that was designed as a solution to the challenge of efficiently storing data generated by data-intensive applications running at large scales. We have built the BlobSeer File System (BSFS), with the goal of providing high throughput under heavy concurrency to MapReduce applications. We also study several aspects related to intermediate data management in MapReduce frameworks. We investigate the requirements of MapReduce intermediate data at two levels: inside the same job, and during the execution of pipeline applications. Finally, we show how BSFS can enable extensions to the de facto MapReduce implementation, Hadoop, such as the support for the append operation. This work also comprises the evaluation and the obtained results in the context of grid and cloud environments
Tsafack, Chetsa Ghislain Landry. « System Profiling and Green Capabilities for Large Scale and Distributed Infrastructures ». Phd thesis, Ecole normale supérieure de lyon - ENS LYON, 2013. http://tel.archives-ouvertes.fr/tel-00946583.
Texte intégralRais, Issam. « Discover, model and combine energy leverages for large scale energy efficient infrastructures ». Thesis, Lyon, 2018. http://www.theses.fr/2018LYSEN051/document.
Texte intégralEnergy consumption is a growing concern on the verge of Exascale computing, a machine reaching 10^18 operations per seconds, 10 times the actual best public supercomputers, it became a crucial focus. Data centers consumed about 7% of total demand of electricity and are responsible of 2% of global carbon emission. With the multiplication of connected devices per person around the world, reducing the energy consumption of large scale computing system is a mandatory step to address in order to build a sustainable digital society.Several techniques, that we call leverage, have been developed in order to lower the electricalconsumption of computing facilities. To face this growing concern many solutions have beendeveloped at multiple levels of computing facilities: infrastructure, hardware, middle-ware, andapplication.It is urgent to embrace energy efficiency as a major concern of our modern computing facilities. Using these leverages is mandatory to better energy efficiency. A lot of leverages are available on large scale computing center. In spite of their potential gains, users and administrators don't fully use them or don't use them at all to better energy efficiency. Although, using these techniques, alone and combined, could be complicated and counter productive if not wisely used.This thesis defines and investigates the discovery, understanding and smart usage of leverages available on a large scale data center or supercomputer. We focus on various single leverages and understand them. We then combine them to other leverages and propose a generic solution to the dynamic usage of combined leverages
KAMMOUH, OMAR. « Resilience assessment of Physical infrastructures and social systems of large scale communities ». Doctoral thesis, Politecnico di Torino, 2019. http://hdl.handle.net/11583/2735173.
Texte intégralBraun, Johannes [Verfasser], Johannes [Akademischer Betreuer] Buchmann et Max [Akademischer Betreuer] Mühlhäuser. « Maintaining Security and Trust in Large Scale Public Key Infrastructures / Johannes Braun. Betreuer : Johannes Buchmann ; Max Mühlhäuser ». Darmstadt : Universitäts- und Landesbibliothek Darmstadt, 2015. http://d-nb.info/1111113351/34.
Texte intégralEsteves, José Jurandir Alves. « Optimization of network slice placement in distributed large-scale infrastructures : from heuristics to controlled deep reinforcement learning ». Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS325.
Texte intégralThis PhD thesis investigates how to optimize Network Slice Placement in distributed large-scale infrastructures focusing on online heuristic and Deep Reinforcement Learning (DRL) based approaches. First, we rely on Integer Linear Programming (ILP) to propose a data model for enabling on-Edge and on-Network Slice Placement. In contrary to most studies related to placement in the NFV context, the proposed ILP model considers complex Network Slice topologies and pays special attention to the geographic location of Network Slice Users and its impact on the End-to-End (E2E) latency. Extensive numerical experiments show the relevance of taking into account the user location constraints. Then, we rely on an approach called the “Power of Two Choices"(P2C) to propose an online heuristic algorithm for the problem which is adapted to support placement on large-scale distributed infrastructures while integrating Edge-specific constraints. The evaluation results show the good performance of the heuristic that solves the problem in few seconds under a large-scale scenario. The heuristic also improves the acceptance ratio of Network Slice Placement Requests when compared against a deterministic online ILP-based solution. Finally, we investigate the use of ML methods, more specifically DRL, for increasing scalability and automation of Network Slice Placement considering a multi-objective optimization approach to the problem. We first propose a DRL algorithm for Network Slice Placement which relies on the Advantage Actor Critic algorithm for fast learning, and Graph Convolutional Networks for feature extraction automation. Then, we propose an approach we call Heuristically Assisted Deep Reinforcement Learning (HA-DRL), which uses heuristics to control the learning and execution of the DRL agent. We evaluate this solution trough simulations under stationary, cycle-stationary and non-stationary network load conditions. The evaluation results show that heuristic control is an efficient way of speeding up the learning process of DRL, achieving a substantial gain in resource utilization, reducing performance degradation, and is more reliable under unpredictable changes in network load than non-controlled DRL algorithms
Rosa, Marcos Leite [Verfasser], Sophie [Akademischer Betreuer] Wolfrum et Joana Carla Soares [Akademischer Betreuer] Goncalves. « From modern infrastructures to operational networks. : The qualification of local space at existing large scale utility infrastructure : a method for reading community-driven initiatives. The case of São Paulo. / Marcos Leite Rosa. Betreuer : Sophie Wolfrum. Gutachter : Joana Carla Soares Goncalves ; Sophie Wolfrum ». München : Universitätsbibliothek der TU München, 2015. http://d-nb.info/1081488069/34.
Texte intégralLivres sur le sujet "Large-scale infrastructures"
Quesnel, Flavien. Scheduling of Large-Scale Virtualized Infrastructures. Hoboken, NJ, USA : John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.
Texte intégralRippa, Alessandro. Borderland Infrastructures. NL Amsterdam : Amsterdam University Press, 2020. http://dx.doi.org/10.5117/9789463725606.
Texte intégralTELESIS, Commission of the European Communities. et Roundtable of European Industrialists, dir. Promoting and financing large scale infrastructure projects in Europe : A report. [s.l.] : TELESIS, 1986.
Trouver le texte intégral1918-, Davidson Frank Paul, Frankel Ernst G et Meador C. Lawrence, dir. Macro-engineering : MIT Brunel lectures on global infrastructure. Chichester : Horwood Pub., 1997.
Trouver le texte intégralGreenstein, Shane M. The evolution of advanced large scale information infrastructure in the United States. Cambridge, MA : National Bureau of Economic Research, 1997.
Trouver le texte intégralForum, GRIPS Development. Linking economic growth and poverty reduction : Large-scale infrastructure in the context of Vietnam's CPRGS. Tokyo : GRIPS, Development Forum, 2003.
Trouver le texte intégralMeera, Shekar, Heaver Richard 1952-, Lee Yi-Kyoung et World Bank, dir. Repositioning nutrition as central to the development agenda : A strategy for large scale action. Washington, D.C : World Bank, 2005.
Trouver le texte intégralCity and port : Urban planning as a cultural venture in London, Barcelona, New York, and Rotterdam : changing relations between public urban space and large-scale infrastructure. Utrecht : International Books, 1999.
Trouver le texte intégralMeyer, Han. City and port : Urban planning as a cultural venture in London, Barcelona, New York, and Rotterdam : changing relations between public urban space and large-scale infrastructure. Utrecht : International Books, 1999.
Trouver le texte intégralRowedder, Simon. Cross-Border Traders in Northern Laos. Nieuwe Prinsengracht 89 1018 VR Amsterdam Nederland : Amsterdam University Press, 2022. http://dx.doi.org/10.5117/9789463722360.
Texte intégralChapitres de livres sur le sujet "Large-scale infrastructures"
Quesnel, Flavien. « Distributed Infrastructures Before the Rise of Virtualization ». Dans Scheduling of Large-Scale Virtualized Infrastructures, 1–12. Hoboken, NJ, USA : John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.ch1.
Texte intégralQuesnel, Flavien. « Contributions of Virtualization ». Dans Scheduling of Large-Scale Virtualized Infrastructures, 13–26. Hoboken, NJ, USA : John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.ch2.
Texte intégralQuesnel, Flavien. « Virtual Infrastructure Managers Used in Production ». Dans Scheduling of Large-Scale Virtualized Infrastructures, 27–47. Hoboken, NJ, USA : John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.ch3.
Texte intégralQuesnel, Flavien. « Comparative Study Between Virtual Infrastructure Managers and Distributed Operating Systems ». Dans Scheduling of Large-Scale Virtualized Infrastructures, 49–65. Hoboken, NJ, USA : John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.ch4.
Texte intégralQuesnel, Flavien. « Dynamic Scheduling of Virtual Machines ». Dans Scheduling of Large-Scale Virtualized Infrastructures, 67–81. Hoboken, NJ, USA : John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.ch5.
Texte intégralQuesnel, Flavien. « DVMS : A Proposal to Schedule Virtual Machines in a Cooperative and Reactive Way ». Dans Scheduling of Large-Scale Virtualized Infrastructures, 83–100. Hoboken, NJ, USA : John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.ch6.
Texte intégralQuesnel, Flavien. « Experimental Protocol and Testing Environment ». Dans Scheduling of Large-Scale Virtualized Infrastructures, 101–11. Hoboken, NJ, USA : John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.ch7.
Texte intégralQuesnel, Flavien. « Experimental Results and Validation of DVMS ». Dans Scheduling of Large-Scale Virtualized Infrastructures, 113–31. Hoboken, NJ, USA : John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.ch8.
Texte intégralQuesnel, Flavien. « Perspectives Around DVMS ». Dans Scheduling of Large-Scale Virtualized Infrastructures, 133–40. Hoboken, NJ, USA : John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.ch9.
Texte intégralJiang, Lifen, Jiang Jiang, Junyi Liang, Kevin R. Wilcox, Scott L. Collins, Alan K. Knapp, William T. Pockman, Melinda D. Smith et Yiqi Luo. « Frontiers of Ecosystem Modeling and Large-Scale Experiments ». Dans Terrestrial Ecosystem Research Infrastructures, 137–62. Boca Raton, FL : CRC Press, 2017. : CRC Press, 2017. http://dx.doi.org/10.1201/9781315368252-8.
Texte intégralActes de conférences sur le sujet "Large-scale infrastructures"
Sanjuàs-Cuxart, Josep, Pere Barlet-Ros, Gianluca Iannaccone et Josep Solé-Pareta. « Distributed scheduling in large scale monitoring infrastructures ». Dans the 2008 ACM CoNEXT Conference. New York, New York, USA : ACM Press, 2008. http://dx.doi.org/10.1145/1544012.1544065.
Texte intégralHelmholt, K., et W. Courage. « Risk management in large scale underground infrastructures ». Dans 2013 7th Annual IEEE Systems Conference (SysCon). IEEE, 2013. http://dx.doi.org/10.1109/syscon.2013.6549991.
Texte intégralKranzlmuller, Dieter. « Management of Large-Scale e-Infrastructures at LRZ ». Dans 2011 22nd International Conference on Database and Expert Systems Applications (DEXA). IEEE, 2011. http://dx.doi.org/10.1109/dexa.2011.49.
Texte intégralCapizzi, Sirio, et Antonio Messina. « A Tuple Space Service for Large Scale Infrastructures ». Dans 2008 IEEE 17th Workshop on Enabling Technologies : Infrastructure for Collaborative Enterprises. IEEE, 2008. http://dx.doi.org/10.1109/wetice.2008.14.
Texte intégralRoutray, Ramani, Rui Zhang, David Eyers, Douglas Willcocks, Peter Pietzuch et Prasenjit Sarkar. « Policy Generation Framework for Large-Scale Storage Infrastructures ». Dans 2010 IEEE International Symposium on Policies for Distributed Systems and Networks. IEEE, 2010. http://dx.doi.org/10.1109/policy.2010.30.
Texte intégralNguyen, Hoang, et Klara Nahrstedt. « Attack Containment Framework for Large-Scale Critical Infrastructures ». Dans 2007 16th International Conference on Computer Communications and Networks. IEEE, 2007. http://dx.doi.org/10.1109/icccn.2007.4317859.
Texte intégralFicco, Massimo, Giovanni Avolio, Luigi Battaglia et Vittorio Manetti. « Hybrid Simulation of Distributed Large-Scale Critical Infrastructures ». Dans 2014 International Conference on Intelligent Networking and Collaborative Systems (INCoS). IEEE, 2014. http://dx.doi.org/10.1109/incos.2014.35.
Texte intégralMontagnat, Johan, Tristan Glatard, Damien Reimert, Ketan Maheshwari, Eddy Caron et Frederic Desprez. « Workflow-based comparison of two Distributed Computing Infrastructures ». Dans 2010 5th Workshop on Workflows in Support of Large-Scale Science (WORKS). IEEE, 2010. http://dx.doi.org/10.1109/works.2010.5671856.
Texte intégralSevegnani, Michele, Milan Kabac, Muffy Calder et Julie McCann. « Modelling and Verification of Large-Scale Sensor Network Infrastructures ». Dans 2018 23rd International Conference on Engineering of Complex Computer Systems (ICECCS). IEEE, 2018. http://dx.doi.org/10.1109/iceccs2018.2018.00016.
Texte intégralLeung, Kin K. « Reinforcement Learning for Large-Scale Communications and Computer Infrastructures ». Dans The 7th World Congress on Electrical Engineering and Computer Systems and Science. Avestia Publishing, 2021. http://dx.doi.org/10.11159/cist21.001.
Texte intégralRapports d'organisations sur le sujet "Large-scale infrastructures"
Taylor, Stephen. Large-Scale Scientific Data-Analysis and Infrastructure. Fort Belvoir, VA : Defense Technical Information Center, décembre 1995. http://dx.doi.org/10.21236/ada310444.
Texte intégralJahanian, Farnam. Detecting and Surviving Large-Scale Network Infrastructure Attacks. Fort Belvoir, VA : Defense Technical Information Center, avril 2005. http://dx.doi.org/10.21236/ada433781.
Texte intégralManmatha, R., J. Allan, W. B. Croft et J. Callan. Infrastructure of Large Scale Multimedia Information Indexing Retrieval and Organization. Fort Belvoir, VA : Defense Technical Information Center, mai 2000. http://dx.doi.org/10.21236/ada379846.
Texte intégralGreenstein, Shane, Mercedes Lizardo et Pablo Spiller. The Evolution of Advanced Large Scale Information Infrastructure in the United States. Cambridge, MA : National Bureau of Economic Research, février 1997. http://dx.doi.org/10.3386/w5929.
Texte intégralDoo, Johnny. Unsettled Issues Concerning eVTOL for Rapid-response, On-demand Firefighting. SAE International, août 2021. http://dx.doi.org/10.4271/epr2021017.
Texte intégralPerera, Duminda, Vladimir Smakhtin, Spencer Williams, Taylor North et Allen Curry. Ageing Water Storage Infrastructure : An Emerging Global Risk. United Nations University Institute for Water, Environment and Health, janvier 2021. http://dx.doi.org/10.53328/qsyl1281.
Texte intégralCialone, Mary, Jessamin Straub, Britt Raubenheimer, Jenna Brown, Katherine Brodie, Nicole Elko, Patrick Dickhudt et al. A large-scale community storm processes field experiment : the During Nearshore Event Experiment (DUNEX) overview reference report. Engineer Research and Development Center (U.S.), mars 2023. http://dx.doi.org/10.21079/11681/46548.
Texte intégralMotamed, Ramin, David McCallen et Swasti Saxena. An International Workshop on Large-Scale Shake Table Testing for the Assessment of Soil-Foundation-Structure System Response for Seismic Safety of DOE Nuclear Facilities, A Virtual Workshop – 17-18 May 2021. Pacific Earthquake Engineering Research Center, University of California, Berkeley, CA, février 2024. http://dx.doi.org/10.55461/jjvo9762.
Texte intégralMuniz Costa, Sérgio Paulo, Gala Gómez Minujín, Paolo Giordano, Juan Pedro Brandi, Jorge Lucángeli, Nilo Meza Monge, Daniel Berrettoni, Irasema Infante et Ricardo Carciofi. Integration & ; Trade Journal : Volume 16 : No. 34 : January-June, 2012. Inter-American Development Bank, mai 2012. http://dx.doi.org/10.18235/0008076.
Texte intégralCampbell, James, Spyros Foteinis, Mohammad Madankan et Phil Renforth. Report on the detailed life cycle analysis results of the two case studies : ocean alkalinity enhancement potential of Spain. OceanNets, juillet 2023. http://dx.doi.org/10.3289/oceannets_d6.4.
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