Literatura científica selecionada sobre o tema "Large-scale infrastructures"
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Artigos de revistas sobre o assunto "Large-scale infrastructures"
Lui, P. C., e T. S. Tan. "Building Integrated Large-Scale Urban Infrastructures: Singapore's Experience". Journal of Urban Technology 8, n.º 1 (abril de 2001): 49–68. http://dx.doi.org/10.1080/10630730120052172.
Texto completo da fonteMarian, BABIK, FEDORKO Ivan, HOOK Nicholas, LANSDALE Thomas Hector, LENKES Daniel, SIKET Miroslav e WALDRON Denis. "LEMON - LHC Era Monitoring for Large-Scale Infrastructures". Journal of Physics: Conference Series 331, n.º 5 (23 de dezembro de 2011): 052025. http://dx.doi.org/10.1088/1742-6596/331/5/052025.
Texto completo da fonteFilelis-Papadopoulos, Christos K., George A. Gravvanis e Panagiotis E. Kyziropoulos. "A framework for simulating large scale cloud infrastructures". Future Generation Computer Systems 79 (fevereiro de 2018): 703–14. http://dx.doi.org/10.1016/j.future.2017.06.017.
Texto completo da fonteRammelt, Crelis. "Infrastructures as Catalysts: Precipitating Uneven Patterns of Development from Large-Scale Infrastructure Investments". Sustainability 10, n.º 4 (22 de abril de 2018): 1286. http://dx.doi.org/10.3390/su10041286.
Texto completo da fonteLan, Cheng Ming, e Wen Feng Liu. "Structural Health Monitoring Cloud and its Applications for Large-Scale Infrastructures". Applied Mechanics and Materials 330 (junho de 2013): 418–25. http://dx.doi.org/10.4028/www.scientific.net/amm.330.418.
Texto completo da fonteGehl, Robert, e Fenwick McKelvey. "Bugging out: darknets as parasites of large-scale media objects". Media, Culture & Society 41, n.º 2 (20 de dezembro de 2018): 219–35. http://dx.doi.org/10.1177/0163443718818379.
Texto completo da fonteBabik, Marian, Ivan Fedorko e David Rodrigues. "Cluman: Advanced cluster management for the large-scale infrastructures". Journal of Physics: Conference Series 331, n.º 5 (23 de dezembro de 2011): 052002. http://dx.doi.org/10.1088/1742-6596/331/5/052002.
Texto completo da fonteTan, Yongmin, Vinay Venkatesh e Xiaohui Gu. "Resilient Self-Compressive Monitoring for Large-Scale Hosting Infrastructures". IEEE Transactions on Parallel and Distributed Systems 24, n.º 3 (março de 2013): 576–86. http://dx.doi.org/10.1109/tpds.2012.167.
Texto completo da fonteNicolae, Bogdan, Gabriel Antoniu, Luc Bougé, Diana Moise e Alexandra Carpen-Amarie. "BlobSeer: Next-generation data management for large scale infrastructures". Journal of Parallel and Distributed Computing 71, n.º 2 (fevereiro de 2011): 169–84. http://dx.doi.org/10.1016/j.jpdc.2010.08.004.
Texto completo da fonteDutta, Kaushik, Debra VanderMeer e Krithi Ramamritham. "Managing RFID events in large-scale distributed RFID infrastructures". Information Technology and Management 12, n.º 3 (3 de fevereiro de 2011): 253–72. http://dx.doi.org/10.1007/s10799-011-0085-6.
Texto completo da fonteTeses / dissertações sobre o assunto "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.
Texto completo da fonteCapizzi, Sirio <1980>. "A tuple space implementation for large-scale infrastructures". Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2008. http://amsdottorato.unibo.it/914/.
Texto completo da fonteGattoni, Gaia. "Analysis of the infrastructures to build immersive visit at large scale". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2022.
Encontre o texto completo da fonteMoise, 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.
Texto completo da fonteData-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.
Texto completo da fonteRais, Issam. "Discover, model and combine energy leverages for large scale energy efficient infrastructures". Thesis, Lyon, 2018. http://www.theses.fr/2018LYSEN051/document.
Texto completo da fonteEnergy 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.
Texto completo da fonteBraun, Johannes [Verfasser], Johannes [Akademischer Betreuer] Buchmann e 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.
Texto completo da fonteEsteves, 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.
Texto completo da fonteThis 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 e 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.
Texto completo da fonteLivros sobre o assunto "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.
Texto completo da fonteRippa, Alessandro. Borderland Infrastructures. NL Amsterdam: Amsterdam University Press, 2020. http://dx.doi.org/10.5117/9789463725606.
Texto completo da fonteTELESIS, Commission of the European Communities. e Roundtable of European Industrialists, eds. Promoting and financing large scale infrastructure projects in Europe: A report. [s.l.]: TELESIS, 1986.
Encontre o texto completo da fonte1918-, Davidson Frank Paul, Frankel Ernst G e Meador C. Lawrence, eds. Macro-engineering: MIT Brunel lectures on global infrastructure. Chichester: Horwood Pub., 1997.
Encontre o texto completo da fonteGreenstein, Shane M. The evolution of advanced large scale information infrastructure in the United States. Cambridge, MA: National Bureau of Economic Research, 1997.
Encontre o texto completo da fonteForum, GRIPS Development. Linking economic growth and poverty reduction: Large-scale infrastructure in the context of Vietnam's CPRGS. Tokyo: GRIPS, Development Forum, 2003.
Encontre o texto completo da fonteMeera, Shekar, Heaver Richard 1952-, Lee Yi-Kyoung e World Bank, eds. Repositioning nutrition as central to the development agenda: A strategy for large scale action. Washington, D.C: World Bank, 2005.
Encontre o texto completo da fonteCity 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.
Encontre o texto completo da fonteMeyer, 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.
Encontre o texto completo da fonteRowedder, 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.
Texto completo da fonteCapítulos de livros sobre o assunto "Large-scale infrastructures"
Quesnel, Flavien. "Distributed Infrastructures Before the Rise of Virtualization". In Scheduling of Large-Scale Virtualized Infrastructures, 1–12. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.ch1.
Texto completo da fonteQuesnel, Flavien. "Contributions of Virtualization". In Scheduling of Large-Scale Virtualized Infrastructures, 13–26. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.ch2.
Texto completo da fonteQuesnel, Flavien. "Virtual Infrastructure Managers Used in Production". In Scheduling of Large-Scale Virtualized Infrastructures, 27–47. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.ch3.
Texto completo da fonteQuesnel, Flavien. "Comparative Study Between Virtual Infrastructure Managers and Distributed Operating Systems". In Scheduling of Large-Scale Virtualized Infrastructures, 49–65. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.ch4.
Texto completo da fonteQuesnel, Flavien. "Dynamic Scheduling of Virtual Machines". In Scheduling of Large-Scale Virtualized Infrastructures, 67–81. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.ch5.
Texto completo da fonteQuesnel, Flavien. "DVMS: A Proposal to Schedule Virtual Machines in a Cooperative and Reactive Way". In Scheduling of Large-Scale Virtualized Infrastructures, 83–100. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.ch6.
Texto completo da fonteQuesnel, Flavien. "Experimental Protocol and Testing Environment". In Scheduling of Large-Scale Virtualized Infrastructures, 101–11. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.ch7.
Texto completo da fonteQuesnel, Flavien. "Experimental Results and Validation of DVMS". In Scheduling of Large-Scale Virtualized Infrastructures, 113–31. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.ch8.
Texto completo da fonteQuesnel, Flavien. "Perspectives Around DVMS". In Scheduling of Large-Scale Virtualized Infrastructures, 133–40. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.ch9.
Texto completo da fonteJiang, Lifen, Jiang Jiang, Junyi Liang, Kevin R. Wilcox, Scott L. Collins, Alan K. Knapp, William T. Pockman, Melinda D. Smith e Yiqi Luo. "Frontiers of Ecosystem Modeling and Large-Scale Experiments". In Terrestrial Ecosystem Research Infrastructures, 137–62. Boca Raton, FL : CRC Press, 2017.: CRC Press, 2017. http://dx.doi.org/10.1201/9781315368252-8.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Large-scale infrastructures"
Sanjuàs-Cuxart, Josep, Pere Barlet-Ros, Gianluca Iannaccone e Josep Solé-Pareta. "Distributed scheduling in large scale monitoring infrastructures". In the 2008 ACM CoNEXT Conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1544012.1544065.
Texto completo da fonteHelmholt, K., e W. Courage. "Risk management in large scale underground infrastructures". In 2013 7th Annual IEEE Systems Conference (SysCon). IEEE, 2013. http://dx.doi.org/10.1109/syscon.2013.6549991.
Texto completo da fonteKranzlmuller, Dieter. "Management of Large-Scale e-Infrastructures at LRZ". In 2011 22nd International Conference on Database and Expert Systems Applications (DEXA). IEEE, 2011. http://dx.doi.org/10.1109/dexa.2011.49.
Texto completo da fonteCapizzi, Sirio, e Antonio Messina. "A Tuple Space Service for Large Scale Infrastructures". In 2008 IEEE 17th Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises. IEEE, 2008. http://dx.doi.org/10.1109/wetice.2008.14.
Texto completo da fonteRoutray, Ramani, Rui Zhang, David Eyers, Douglas Willcocks, Peter Pietzuch e Prasenjit Sarkar. "Policy Generation Framework for Large-Scale Storage Infrastructures". In 2010 IEEE International Symposium on Policies for Distributed Systems and Networks. IEEE, 2010. http://dx.doi.org/10.1109/policy.2010.30.
Texto completo da fonteNguyen, Hoang, e Klara Nahrstedt. "Attack Containment Framework for Large-Scale Critical Infrastructures". In 2007 16th International Conference on Computer Communications and Networks. IEEE, 2007. http://dx.doi.org/10.1109/icccn.2007.4317859.
Texto completo da fonteFicco, Massimo, Giovanni Avolio, Luigi Battaglia e Vittorio Manetti. "Hybrid Simulation of Distributed Large-Scale Critical Infrastructures". In 2014 International Conference on Intelligent Networking and Collaborative Systems (INCoS). IEEE, 2014. http://dx.doi.org/10.1109/incos.2014.35.
Texto completo da fonteMontagnat, Johan, Tristan Glatard, Damien Reimert, Ketan Maheshwari, Eddy Caron e Frederic Desprez. "Workflow-based comparison of two Distributed Computing Infrastructures". In 2010 5th Workshop on Workflows in Support of Large-Scale Science (WORKS). IEEE, 2010. http://dx.doi.org/10.1109/works.2010.5671856.
Texto completo da fonteSevegnani, Michele, Milan Kabac, Muffy Calder e Julie McCann. "Modelling and Verification of Large-Scale Sensor Network Infrastructures". In 2018 23rd International Conference on Engineering of Complex Computer Systems (ICECCS). IEEE, 2018. http://dx.doi.org/10.1109/iceccs2018.2018.00016.
Texto completo da fonteLeung, Kin K. "Reinforcement Learning for Large-Scale Communications and Computer Infrastructures". In The 7th World Congress on Electrical Engineering and Computer Systems and Science. Avestia Publishing, 2021. http://dx.doi.org/10.11159/cist21.001.
Texto completo da fonteRelatórios de organizações sobre o assunto "Large-scale infrastructures"
Taylor, Stephen. Large-Scale Scientific Data-Analysis and Infrastructure. Fort Belvoir, VA: Defense Technical Information Center, dezembro de 1995. http://dx.doi.org/10.21236/ada310444.
Texto completo da fonteJahanian, Farnam. Detecting and Surviving Large-Scale Network Infrastructure Attacks. Fort Belvoir, VA: Defense Technical Information Center, abril de 2005. http://dx.doi.org/10.21236/ada433781.
Texto completo da fonteManmatha, R., J. Allan, W. B. Croft e J. Callan. Infrastructure of Large Scale Multimedia Information Indexing Retrieval and Organization. Fort Belvoir, VA: Defense Technical Information Center, maio de 2000. http://dx.doi.org/10.21236/ada379846.
Texto completo da fonteGreenstein, Shane, Mercedes Lizardo e Pablo Spiller. The Evolution of Advanced Large Scale Information Infrastructure in the United States. Cambridge, MA: National Bureau of Economic Research, fevereiro de 1997. http://dx.doi.org/10.3386/w5929.
Texto completo da fonteDoo, Johnny. Unsettled Issues Concerning eVTOL for Rapid-response, On-demand Firefighting. SAE International, agosto de 2021. http://dx.doi.org/10.4271/epr2021017.
Texto completo da fontePerera, Duminda, Vladimir Smakhtin, Spencer Williams, Taylor North e Allen Curry. Ageing Water Storage Infrastructure: An Emerging Global Risk. United Nations University Institute for Water, Environment and Health, janeiro de 2021. http://dx.doi.org/10.53328/qsyl1281.
Texto completo da fonteCialone, 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.), março de 2023. http://dx.doi.org/10.21079/11681/46548.
Texto completo da fonteMotamed, Ramin, David McCallen e 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, fevereiro de 2024. http://dx.doi.org/10.55461/jjvo9762.
Texto completo da fonteMuniz Costa, Sérgio Paulo, Gala Gómez Minujín, Paolo Giordano, Juan Pedro Brandi, Jorge Lucángeli, Nilo Meza Monge, Daniel Berrettoni, Irasema Infante e Ricardo Carciofi. Integration & Trade Journal: Volume 16 : No. 34 : January-June, 2012. Inter-American Development Bank, maio de 2012. http://dx.doi.org/10.18235/0008076.
Texto completo da fonteCampbell, James, Spyros Foteinis, Mohammad Madankan e Phil Renforth. Report on the detailed life cycle analysis results of the two case studies: ocean alkalinity enhancement potential of Spain. OceanNets, julho de 2023. http://dx.doi.org/10.3289/oceannets_d6.4.
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