Relevant bibliographies by topics / Large-scale infrastructures

Academic literature on the topic 'Large-scale infrastructures'

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Published: 25 May 2024

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Journal articles on the topic "Large-scale infrastructures"

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Lui, P. C., and T. S. Tan. "Building Integrated Large-Scale Urban Infrastructures: Singapore's Experience." Journal of Urban Technology 8, no. 1 (April 2001): 49–68. http://dx.doi.org/10.1080/10630730120052172.

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Marian, BABIK, FEDORKO Ivan, HOOK Nicholas, LANSDALE Thomas Hector, LENKES Daniel, SIKET Miroslav, and WALDRON Denis. "LEMON - LHC Era Monitoring for Large-Scale Infrastructures." Journal of Physics: Conference Series 331, no. 5 (December 23, 2011): 052025. http://dx.doi.org/10.1088/1742-6596/331/5/052025.

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Filelis-Papadopoulos, Christos K., George A. Gravvanis, and Panagiotis E. Kyziropoulos. "A framework for simulating large scale cloud infrastructures." Future Generation Computer Systems 79 (February 2018): 703–14. http://dx.doi.org/10.1016/j.future.2017.06.017.

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Rammelt, Crelis. "Infrastructures as Catalysts: Precipitating Uneven Patterns of Development from Large-Scale Infrastructure Investments." Sustainability 10, no. 4 (April 22, 2018): 1286. http://dx.doi.org/10.3390/su10041286.

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Lan, Cheng Ming, and Wen Feng Liu. "Structural Health Monitoring Cloud and its Applications for Large-Scale Infrastructures." Applied Mechanics and Materials 330 (June 2013): 418–25. http://dx.doi.org/10.4028/www.scientific.net/amm.330.418.

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The concept and framework about Structural Health Monitoring Cloud (SHMC) for data management, data storage, safety warning and structural safety assessment are established in this paper based on the fusions of cloud computing, internet of things (IOT), and structural health monitoring (SHM). SHM plays a significant role in modern infrastructure because it provides a means to assess structural integrity online, eliminate manual inspections and may result in a transition from time-to condition-based maintenance. Also, there are many difficulties to deal with the huge amounts data for the owner of infrastructure. So the new ideas of SHMC which is provided and realized by the third part professional organization are proposed in this paper. Based on the summary of the technical characteristic of internet of things for structural health monitoring, the system requirements, architecture, and advantages of SHMC are described, and then the statues of related technology research were reviewed. The data mining and damage detection programs are embedded in SHMC platform and all collected data from acquisition system would be processed and then be used to assess the safety of infrastructures. Finally, actual applications of SHMC for large-scale infrastructures are illustrated.
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Gehl, Robert, and Fenwick McKelvey. "Bugging out: darknets as parasites of large-scale media objects." Media, Culture & Society 41, no. 2 (December 20, 2018): 219–35. http://dx.doi.org/10.1177/0163443718818379.

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Platforms and infrastructures have quickly become seminal concepts to understand large-scale computational systems. The difference between a platform and an infrastructure is subject to debate. In this article, we use the concept of the darknet to describe how infrastructure tends toward being public with other things where platforms tend to private relations. The darknet reveals these relations negatively, as we discuss, by turning these media objects into that which they desire not to be. We analyze these negative relations through the concept of the parasite developed by Michel Serres. By following how darknets parasite both platforms and infrastructure, we suggest a need to develop new concepts to understand the diversity of relations now possible in a network society.
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Babik, Marian, Ivan Fedorko, and David Rodrigues. "Cluman: Advanced cluster management for the large-scale infrastructures." Journal of Physics: Conference Series 331, no. 5 (December 23, 2011): 052002. http://dx.doi.org/10.1088/1742-6596/331/5/052002.

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Tan, Yongmin, Vinay Venkatesh, and Xiaohui Gu. "Resilient Self-Compressive Monitoring for Large-Scale Hosting Infrastructures." IEEE Transactions on Parallel and Distributed Systems 24, no. 3 (March 2013): 576–86. http://dx.doi.org/10.1109/tpds.2012.167.

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Nicolae, Bogdan, Gabriel Antoniu, Luc Bougé, Diana Moise, and Alexandra Carpen-Amarie. "BlobSeer: Next-generation data management for large scale infrastructures." Journal of Parallel and Distributed Computing 71, no. 2 (February 2011): 169–84. http://dx.doi.org/10.1016/j.jpdc.2010.08.004.

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Dutta, Kaushik, Debra VanderMeer, and Krithi Ramamritham. "Managing RFID events in large-scale distributed RFID infrastructures." Information Technology and Management 12, no. 3 (February 3, 2011): 253–72. http://dx.doi.org/10.1007/s10799-011-0085-6.

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Dissertations / Theses on the topic "Large-scale infrastructures"

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Capizzi, Sirio <1980&gt. "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.

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Coordinating activities in a distributed system is an open research topic. Several models have been proposed to achieve this purpose such as message passing, publish/subscribe, workflows or tuple spaces. We have focused on the latter model, trying to overcome some of its disadvantages. In particular we have applied spatial database techniques to tuple spaces in order to increase their performance when handling a large number of tuples. Moreover, we have studied how structured peer to peer approaches can be applied to better distribute tuples on large networks. Using some of these result, we have developed a tuple space implementation for the Globus Toolkit that can be used by Grid applications as a coordination service. The development of such a service has been quite challenging due to the limitations imposed by XML serialization that have heavily influenced its design. Nevertheless, we were able to complete its implementation and use it to implement two different types of test applications: a completely parallelizable one and a plasma simulation that is not completely parallelizable. Using this last application we have compared the performance of our service against MPI. Finally, we have developed and tested a simple workflow in order to show the versatility of our service.
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Capizzi, Sirio <1980&gt. "A tuple space implementation for large-scale infrastructures." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2008. http://amsdottorato.unibo.it/914/.

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Coordinating activities in a distributed system is an open research topic. Several models have been proposed to achieve this purpose such as message passing, publish/subscribe, workflows or tuple spaces. We have focused on the latter model, trying to overcome some of its disadvantages. In particular we have applied spatial database techniques to tuple spaces in order to increase their performance when handling a large number of tuples. Moreover, we have studied how structured peer to peer approaches can be applied to better distribute tuples on large networks. Using some of these result, we have developed a tuple space implementation for the Globus Toolkit that can be used by Grid applications as a coordination service. The development of such a service has been quite challenging due to the limitations imposed by XML serialization that have heavily influenced its design. Nevertheless, we were able to complete its implementation and use it to implement two different types of test applications: a completely parallelizable one and a plasma simulation that is not completely parallelizable. Using this last application we have compared the performance of our service against MPI. Finally, we have developed and tested a simple workflow in order to show the versatility of our service.
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Gattoni, Gaia. "Analysis of the infrastructures to build immersive visit at large scale." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2022.

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This thesis aims to introduce some relevant notion to demonstrate how digital innovation may benefit all phases of the development of a construction project. It has proven possible, through the use of the BIM technique, to optimize the design, construction, and administration phases of structures. With the aid of virtual reality, it is feasible to reproduce a complete immersion experience of the structure during the design phase. The two scenarios illustrated in this thesis need to be considered as two different approaches to technological innovation. From LaVallée project, the first scenario, it can be stated that the BIM methodology applied in this context and then expanded to the concept of CIM is essential for the district's construction. The purpose is to predict and describe the quality of the environment and urban spaces in a project situation and to validate the results obtained. In order to do this, it is necessary to create an immersive visit with 3D modeling of the LaVallée area using BIM data, where these data are collected from different project partners in IFC format. With all of the information I gained from this study, I was able to employ the abilities to a different scenario: the Rimini port. The goal of this final part, is to reconstruct a three-dimensional visualization starting from a very basic level of information, which means looking for methods and tools that can easily represent a virtual visit through the use of 2D data.
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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 production. Une implémentation domaine publique de l'abstraction mise en avant par Google, a été fournie par Yahoo à travers du project Hadoop. Le framework Hadoop est considéré l'implémentation de référence de MapReduce et est actuellement largement utilisé à des fins diverses et sur plusieurs infrastructures. Nous proposons un système de fichiers distribué, optimisé pour des accès hautement concurrents, qui puisse servir comme couche de stockage pour des applications MapReduce. Nous avons conçu le BlobSeer File System (BSFS), basé sur BlobSeer, un service de stockage distribué, hautement efficace, facilitant le partage de données à grande échelle. Nous étudions également plusieurs aspects liés à la gestion des données intermédiaires dans des environnements MapReduce. Nous explorons les contraintes des données intermédiaires MapReduce à deux niveaux: dans le même job MapReduce et pendant l'exécution des pipelines d'applications MapReduce. Enfin, nous proposons des extensions de Hadoop, un environnement MapReduce populaire et open-source, comme par example le support de l'opération append. Ce travail inclut également l'évaluation et les résultats obtenus sur des infrastructures à grande échelle: grilles informatiques et clouds
Data-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
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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.

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Nowadays, reducing the energy consumption of large scale and distributed infrastructures has truly become a challenge for both industry and academia. This is corroborated by the many efforts aiming to reduce the energy consumption of those systems. Initiatives for reducing the energy consumption of large scale and distributed infrastructures can without loss of generality be broken into hardware and software initiatives.Unlike their hardware counterpart, software solutions to the energy reduction problem in large scale and distributed infrastructures hardly result in real deployments. At the one hand, this can be justified by the fact that they are application oriented. At the other hand, their failure can be attributed to their complex nature which often requires vast technical knowledge behind proposed solutions and/or thorough understanding of applications at hand. This restricts their use to a limited number of experts, because users usually lack adequate skills. In addition, although subsystems including the memory are becoming more and more power hungry, current software energy reduction techniques fail to take them into account. This thesis proposes a methodology for reducing the energy consumption of large scale and distributed infrastructures. Broken into three steps known as (i) phase identification, (ii) phase characterization, and (iii) phase identification and system reconfiguration; our methodology abstracts away from any individual applications as it focuses on the infrastructure, which it analyses the runtime behaviour and takes reconfiguration decisions accordingly.The proposed methodology is implemented and evaluated in high performance computing (HPC) clusters of varied sizes through a Multi-Resource Energy Efficient Framework (MREEF). MREEF implements the proposed energy reduction methodology so as to leave users with the choice of implementing their own system reconfiguration decisions depending on their needs. Experimental results show that our methodology reduces the energy consumption of the overall infrastructure of up to 24% with less than 7% performance degradation. By taking into account all subsystems, our experiments demonstrate that the energy reduction problem in large scale and distributed infrastructures can benefit from more than "the traditional" processor frequency scaling. Experiments in clusters of varied sizes demonstrate that MREEF and therefore our methodology can easily be extended to a large number of energy aware clusters. The extension of MREEF to virtualized environments like cloud shows that the proposed methodology goes beyond HPC systems and can be used in many other computing environments.
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Rais, Issam. "Discover, model and combine energy leverages for large scale energy efficient infrastructures." Thesis, Lyon, 2018. http://www.theses.fr/2018LYSEN051/document.

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La consommation énergétique de nos entités de calculs à grande échelle est une problématique de plus en plus inquiétante. Il est d'autant plus inquiétant que nous nous dirigeons vers "L'exascale",machine qui calcule 10^18 opérations flottantes par secondes, soit 10 fois plus que les meilleurs machines publiques actuelles. En 2017, les data-center consommaient 7% de la demande globale et étaient responsable de 2% de l’émission globale de CO2. Avec la multiplication actuelle du nombre d'outils connectés par personne, réduire la consommation énergétique des data-centers et supercalculateurs à grande échelle est une problématique cruciale pour construire une société numérique durable.Il est donc urgent de voir la consommation énergétique comme une problématique phare de cescentres. De nombreuses techniques, ici nommé "levier", ont été développées dans le but de réduire la consommation électrique des centres de calculs, à différents niveaux : infrastructure, matériel, intergiciel et applicatif. Bien utiliser ces leviers est donc capitale pour s'approcher de l'efficience énergétique. Un grand nombre de leviers sont disponibles dans ces centres de calculs. Malgré leurs gains potentiels, il peut être compliqué de bien les utiliser mais aussi d'en combiner plusieurs en restant efficace en énergie.Dans cette thèse, nous avons abordé la découverte, compréhension et usage intelligent des leviers disponibles à grande échelle dans ces centres de calculs. Nous avons étudié des leviers de manière indépendante, puis les avons combinés à d'autres leviers afin de proposer une solution générique et dynamique à l'usage combiné des leviers
Energy 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
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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.

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Braun, Johannes [Verfasser], Johannes [Akademischer Betreuer] Buchmann, and 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.

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Esteves, 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.

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Cette thèse examine comment optimiser le placement de tranches (slices) de réseau dans les infrastructures distribuées à grande échelle en se concentrant sur des approches heuristiques en ligne et basées sur l'apprentissage par renforcement profond (DRL). Tout d'abord, nous nous appuyons sur la programmation linéaire en nombre entiers (ILP) pour proposer un modèle de données permettant le placement de tranches de réseau sur le bord et le cœur du réseau. Contrairement à la plupart des études relatives au placement de fonctions réseau virtualisées, le modèle ILP proposé prend en compte les topologies complexes des tranches de réseau et accorde une attention particulière à l'emplacement géographique des utilisateurs des tranches réseau et à son impact sur le calcul de la latence de bout en bout. Des expérimentations numériques nous ont permis de montrer la pertinence de la prise en compte des contraintes de localisation des utilisateurs.Ensuite, nous nous appuyons sur une approche appelée "Power of Two Choices" pour proposer un algorithme heuristique en ligne qui est adapté à supporter le placement sur des infrastructures distribuées à grande échelle tout en intégrant des contraintes spécifiques au bord du réseau. Les résultats de l'évaluation montrent la bonne performance de l'heuristique qui résout le problème en quelques secondes dans un scénario à grande échelle. L'heuristique améliore également le taux d'acceptation des demandes de placement de tranches de réseau par rapport à une solution déterministe en ligne en utilisant l'ILP.Enfin, nous étudions l'utilisation de méthodes de ML, et plus particulièrement de DRL, pour améliorer l'extensibilité et l'automatisation du placement de tranches réseau en considérant une version multi-objectif du problème. Nous proposons d'abord un algorithme DRL pour le placement de tranches réseau qui s'appuie sur l'algorithme "Advantage Actor Critic" pour un apprentissage rapide, et sur les réseaux convolutionels de graphes pour l'extraction de propriétés. Ensuite, nous proposons une approche que nous appelons "Heuristically Assisted DRL" (HA-DRL), qui utilise des heuristiques pour contrôler l'apprentissage et l'exécution de l'agent DRL. Nous évaluons cette solution par des simulations dans des conditions de charge de réseau stationnaire, ensuite cyclique et enfin non-stationnaire. Les résultats de l'évaluation montrent que le contrôle par heuristique est un moyen efficace d'accélérer le processus d'apprentissage du DRL, et permet d'obtenir un gain substantiel dans l'utilisation des ressources, de réduire la dégradation des performances et d'être plus fiable en cas de changements imprévisibles de la charge du réseau que les algorithmes DRL non contrôlés
This 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
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Rosa, Marcos Leite [Verfasser], Sophie [Akademischer Betreuer] Wolfrum, and 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.

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Books on the topic "Large-scale infrastructures"

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Quesnel, Flavien. Scheduling of Large-Scale Virtualized Infrastructures. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118790335.

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Rippa, Alessandro. Borderland Infrastructures. NL Amsterdam: Amsterdam University Press, 2020. http://dx.doi.org/10.5117/9789463725606.

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Across the Chinese borderlands, investments in large-scale transnational infrastructure such as roads and special economic zones have increased exponentially over the past two decades. Based on long-term ethnographic research, Borderland Infrastructures addresses a major contradiction at the heart of this fast-paced development: small-scale traders have lost their historic strategic advantages under the growth of massive Chinese state investment and are now struggling to keep their businesses afloat. Concurrently, local ethnic minorities have become the target of radical resettlement projects, securitization, and tourism initiatives, and have in many cases grown increasingly dependent on state subsidies. At the juncture of anthropological explorations of the state, border studies, and research on transnational trade and infrastructure development, Borderland Infrastructures provides new analytical tools to understand how state power is experienced, mediated, and enacted in Xinjiang and Yunnan. In the process, Rippa offers a rich and nuanced ethnography of life across China’s peripheries.
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TELESIS, Commission of the European Communities., and Roundtable of European Industrialists, eds. Promoting and financing large scale infrastructure projects in Europe: A report. [s.l.]: TELESIS, 1986.

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1918-, Davidson Frank Paul, Frankel Ernst G, and Meador C. Lawrence, eds. Macro-engineering: MIT Brunel lectures on global infrastructure. Chichester: Horwood Pub., 1997.

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Greenstein, Shane M. The evolution of advanced large scale information infrastructure in the United States. Cambridge, MA: National Bureau of Economic Research, 1997.

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Forum, GRIPS Development. Linking economic growth and poverty reduction: Large-scale infrastructure in the context of Vietnam's CPRGS. Tokyo: GRIPS, Development Forum, 2003.

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Meera, Shekar, Heaver Richard 1952-, Lee Yi-Kyoung, and World Bank, eds. Repositioning nutrition as central to the development agenda: A strategy for large scale action. Washington, D.C: World Bank, 2005.

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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.

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Meyer, 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.

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Rowedder, 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.

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Northern Laos has become a prominent spot in large-scale, top-down mappings and studies of neoliberal globalisation and infrastructural development linking Thailand and China, and markets further beyond. Yet in the common narrative, in which Laos appears as a weak victim helplessly exposed to its larger neighbours, attention is seldom paid to local voices. This book fills this gap. Building on long-term multi-sited fieldwork, it accompanies northern Lao cross-border traders closely in their transnational worlds of mobilities, social relations, economic experimentation and aspiration. Cross-Border Traders in Northern Laos: Mastering Smallness demonstrates that these traders’ indispensable but often invisible role in the everyday workings of the China-Laos-Thailand borderland economy relies on their rhetoric and practices of ‘smallness’—of framing their transnational trade activities in a self-deprecating manner and stressing their economic inferiority. Decoding their discursive surface of insignificance, this ethnography of ‘smallness’ foregrounds remarkable transnational social and economic skills that are mostly invisible in Sino-Southeast Asian borderland scholarship.
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Book chapters on the topic "Large-scale infrastructures"

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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.

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Quesnel, 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.

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Quesnel, 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.

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Quesnel, 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.

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Quesnel, 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.

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Quesnel, 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.

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Quesnel, 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.

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Quesnel, 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.

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Quesnel, 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.

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Jiang, Lifen, Jiang Jiang, Junyi Liang, Kevin R. Wilcox, Scott L. Collins, Alan K. Knapp, William T. Pockman, Melinda D. Smith, and 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.

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Conference papers on the topic "Large-scale infrastructures"

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Sanjuàs-Cuxart, Josep, Pere Barlet-Ros, Gianluca Iannaccone, and 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.

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Helmholt, K., and 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.

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Kranzlmuller, 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.

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Capizzi, Sirio, and 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.

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Routray, Ramani, Rui Zhang, David Eyers, Douglas Willcocks, Peter Pietzuch, and 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.

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Nguyen, Hoang, and 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.

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Ficco, Massimo, Giovanni Avolio, Luigi Battaglia, and 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.

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Montagnat, Johan, Tristan Glatard, Damien Reimert, Ketan Maheshwari, Eddy Caron, and 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.

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Sevegnani, Michele, Milan Kabac, Muffy Calder, and 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.

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Leung, 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.

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Reports on the topic "Large-scale infrastructures"

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Taylor, Stephen. Large-Scale Scientific Data-Analysis and Infrastructure. Fort Belvoir, VA: Defense Technical Information Center, December 1995. http://dx.doi.org/10.21236/ada310444.

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Jahanian, Farnam. Detecting and Surviving Large-Scale Network Infrastructure Attacks. Fort Belvoir, VA: Defense Technical Information Center, April 2005. http://dx.doi.org/10.21236/ada433781.

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Manmatha, R., J. Allan, W. B. Croft, and J. Callan. Infrastructure of Large Scale Multimedia Information Indexing Retrieval and Organization. Fort Belvoir, VA: Defense Technical Information Center, May 2000. http://dx.doi.org/10.21236/ada379846.

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Greenstein, Shane, Mercedes Lizardo, and Pablo Spiller. The Evolution of Advanced Large Scale Information Infrastructure in the United States. Cambridge, MA: National Bureau of Economic Research, February 1997. http://dx.doi.org/10.3386/w5929.

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Doo, Johnny. Unsettled Issues Concerning eVTOL for Rapid-response, On-demand Firefighting. SAE International, August 2021. http://dx.doi.org/10.4271/epr2021017.

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Recent advancements of electric vertical take-off and landing (eVTOL) aircraft have generated significant interest within and beyond the traditional aviation industry, and many novel applications have been identified and are in development. One promising application for these innovative systems is in firefighting, with eVTOL aircraft complementing current firefighting capabilities to help save lives and reduce fire-induced damages. With increased global occurrences and scales of wildfires—not to mention the issues firefighters face during urban and rural firefighting operations daily—eVTOL technology could offer timely, on-demand, and potentially cost-effective aerial mobility capabilities to counter these challenges. Early detection and suppression of wildfires could prevent many fires from becoming large-scale disasters. eVTOL aircraft may not have the capacity of larger aerial assets for firefighting, but targeted suppression, potentially in swarm operations, could be valuable. Most importantly, on-demand aerial extraction of firefighters can be a crucial benefit during wildfire control operations. Aerial firefighter dispatch from local fire stations or vertiports can result in more effective operations, and targeted aerial fire suppression and civilian extraction from high-rise buildings could enhance capabilities significantly. There are some challenges that need to be addressed before the identified capabilities and benefits are realized at scale, including the development of firefighting-specific eVTOL vehicles; sense and avoid capabilities in complex, smoke-inhibited environments; autonomous and remote operating capabilities; charging system compatibility and availability; operator and controller training; dynamic airspace management; and vehicle/fleet logistics and support. Acceptance from both the first-responder community and the general public is also critical for the successful implementation of these new capabilities. The purpose of this report is to identify the benefits and challenges of implementation, as well as some of the potential solutions. Based on the rapid development progress of eVTOL aircraft and infrastructures with proactive community engagement, it is envisioned that these challenges can be addressed soon. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. These reports are not intended to resolve the challenges they identify or close any topic to further scrutiny.
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Perera, Duminda, Vladimir Smakhtin, Spencer Williams, Taylor North, and Allen Curry. Ageing Water Storage Infrastructure: An Emerging Global Risk. United Nations University Institute for Water, Environment and Health, January 2021. http://dx.doi.org/10.53328/qsyl1281.

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The Report provides an overview of the current state of knowledge on the ageing of large dams –an emerging global development issue as tens of thousands of existing large dams have reached or exceeded an “alert” age threshold of 50 years, and many others will soon approach 100 years. These aged structures incur rapidly rising maintenance needs and costs while simultaneously declining their effectiveness and posing potential threats to human safety and the environment. The Report analyzes large dam construction trends across major geographical regions and primary dam functions, such as water supply, irrigation, flood control, hydropower, and recreation. Analysis of existing global datasets indicates that despite plans in some regions and countries to build more water storage dams, particularly for hydropower generation, there will not be another “dam revolution” to match the scale of the high-intensity dam construction experienced in the early to middle, 20th century. At the same time, many of the large dams constructed then are aging, and hence we are already experiencing a “mass ageing” of water storage infrastructure. The Report further explores the emerging practice of decommissioning ageing dams, which can be removal or re-operation, to address issues of ensuring public safety, escalating maintenance costs, reservoir sedimentation, and restoration of a natural river ecosystem. Decommissioning becomes the option if economic and practical limitations prevent a dam from being upgraded or if its original use has become obsolete. The cost of dam removal is estimated to be an order of magnitude less than that of repairing. The Report also gives an overview of dam decommissioning’s socio-economic impacts, including those on local livelihoods, heritage, property value, recreation, and aesthetics. Notably, the nature of these impacts varies significantly between low- and high-income countries. The Report shows that while dam decommissioning is a relatively recent phenomenon, it is gaining pace in the USA and Europe, where many dams are older. However, it is primarily small dams that have been removed to date, and the decommissioning of large dams is still in its infancy, with only a few known cases in the last decade. A few case studies of ageing and decommissioned large dams illustrate the complexity and length of the process that is often necessary to orchestrate the dam removal safely. Even removing a small dam requires years (often decades), continuous expert and public involvement, and lengthy regulatory reviews. With the mass ageing of dams well underway, it is important to develop a framework of protocols that will guide and accelerate the process of dam removal. Overall, the Report aims to attract global attention to the creeping issue of ageing water storage infrastructure and stimulate international efforts to deal with this emerging water risk. This Report’s primary target audiences are governments and their partners responsible for planning and implementing water infrastructure development and management, emphasizing adaptat
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Cialone, 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.), March 2023. http://dx.doi.org/10.21079/11681/46548.

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The DUring Nearshore Event EXperiment (DUNEX) was a series of large-scale nearshore coastal field experiments focused on during-storm, nearshore coastal processes. The experiments were conducted on the North Carolina coast by a multidisciplinary group of over 30 research scientists from 2019 to 2021. The overarching goal of DUNEX was to collaboratively gather information to improve understanding of the interactions of coastal water levels, waves, and flows, beach and dune evolution, soil behavior, vegetation, and groundwater during major coastal storms that affect infrastructure, habitats, and communities. In the short term, these high-quality field measurements will lead to better understanding of during-storm processes, impacts and post-storm recovery and will enhance US academic coastal research programs. Longer-term, DUNEX data and outcomes will improve understanding and prediction of extreme event physical processes and impacts, validate coastal processes numerical models, and improve coastal resilience strategies and communication methods for coastal communities impacted by storms. This report focuses on the planning and preparation required to conduct a large-scale field experiment, the collaboration amongst researchers, and lessons learned. The value of a large-scale experiment focused on storm processes and impacts begins with the scientific gains from the data collected, which will be available and used for decades to come.
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Motamed, Ramin, David McCallen, and 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, February 2024. http://dx.doi.org/10.55461/jjvo9762.

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Aging infrastructure within the US Department of Energy (DOE) and the National Nuclear Security Administration (NNSA) nuclear facilities poses a major challenge to their resiliency against natural phenomenon hazards. Examples of mission-critical facilities located in regions of high seismicity can be found at a number of NNSA sites including Lawrence Livermore National Laboratory, Los Alamos National Laboratory, and the Nevada National Security Site. Most of the nation’s currently operating nuclear facilities have already reached their operating lifetime, and most currently operating nuclear power plants (NPPs) have already reached the extent of their operating license period. While the domestic demand for electrical energy is expected to grow, if currently operating NPPs do not extend their operations and additional plants are not built quickly enough to replace them, the total fraction of electrical energy generated from carbon-free nuclear power will rapidly decline. The decision to extend operation is ultimately an economic one; however, economics can often be improved through technical advancements (McCarthy et al. 2015) and research and development (R&D) activities. Similarly, the operating lifetime of the current DOE- and NNSA-owned critical infrastructure can be extended using the Probabilistic Risk Assessment (PRA) framework to systematically identify the risk associated with designing and operating existing facilities and building new ones. Using this framework consists of several steps, including (1) system analysis considering the interaction between components, such as evaluating the soil-foundation-structure system response; and (2) assessment of areas of uncertainty. Both of these steps are essential to assessing and reducing risks to the DOE and NNSA nuclear facilities. While the risks to the DOE’s facilities are primarily due to natural hazard phenomena, data from large-scale tests of the soil-foundation-structural system response to seismic shaking is currently lacking. This workshop aimed to address these key areas by organizing an international workshop focused on advancing the seismic safety of nuclear facilities using large-scale shake table testing. As a result, this workshop, which was held virtually, brought together a select group of international experts in large-scale shake table testing from the U.S., Japan, and Europe to discuss state-of-the-art experimental techniques and emerging instrumentation technologies that can produce unique experimental data to advance knowledge in natural hazards that impact the safety of the DOE’s nuclear facilities. The generated experimental data followed by research and development activities will ultimately result in updates to ASCE 4-16, one of the primary design guides for DOE nuclear facilities per DOE-STD-1020-2016. The ultimate objective of the workshop was to develop a “road map” for the future experimental campaign and innovative instrumentations using the newly constructed DOE-funded large-scale shake table facility at the University of Nevada, Reno (UNR) as well as other large-scale shake table testing facilities. This new facility resulted from a collaborative project engagement between UNR and Lawrence Berkeley National Laboratory. (LBNL). This report summarizes the proceedings of the workshop and highlights the key outcomes from presentations and discussions.
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Muniz Costa, Sérgio Paulo, Gala Gómez Minujín, Paolo Giordano, Juan Pedro Brandi, Jorge Lucángeli, Nilo Meza Monge, Daniel Berrettoni, Irasema Infante, and Ricardo Carciofi. Integration & Trade Journal: Volume 16 : No. 34 : January-June, 2012. Inter-American Development Bank, May 2012. http://dx.doi.org/10.18235/0008076.

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This issue of the Journal is devoted to physical integration in Latin America. The Editorial Committee set about designing the contents, with a call for papers, which suggested topics and questions that focused on the subject while covering a broad spectrum. Regional physical integration is supported by a wide range of instruments; such as infrastructure works to reduce transportation costs and enhance connectivity, and financial structuring of technically, highly complex large scale capital investments. But no less relevant are government cooperation mechanisms that provide the necessary coordination for trade facilitation policies and measures, or the local impacts associated with enterprises, especially those located in border areas.
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Campbell, James, Spyros Foteinis, Mohammad Madankan, and Phil Renforth. Report on the detailed life cycle analysis results of the two case studies: ocean alkalinity enhancement potential of Spain. OceanNets, July 2023. http://dx.doi.org/10.3289/oceannets_d6.4.

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A common challenge in many ocean-based negative emissions technologies (NETs) is the difficulty of developing new global industries and supply chains, which could be necessary for their much needed rapid and large-scale deployment. Therefore, to facilitate roll-out, existing industries and infrastructure should preferably be utilised. For ocean alkalinity enhancement (OAE) by CaO, i.e., ocean liming (OL), the lime can be produced by calcination of limestone using the spare capacity in the cement industry. For OAE by NaOH, i.e., electrochemical brine splitting (EBS), the NaOH can be produced by electrolysis of waste brines from the desalination sector. In this case study, we investigate the realistic OAE potential of Spain, because of its large availability of limestone, its increasing spare cement kiln capacity, and its large and growing desalination industry. This case study shows Spain has a high potential for alkalinity addition to the oceans. Specifically, the total CDR capacity of Spain via OAE is 24.4 Mt yr.-1 with contributions of 22.6 Mt of CO2 removed by OL and 1.8 Mt of CO2 removed by EBS, assuming these processes are driven solely by renewable energy. Further, this case study provides a realistic estimate of the CO2 removal potential and life cycle emissions for alkalinity enhancement for a given region, in contrast to more general global or continental studies before it. By doing so, Spain’s annual carbon dioxide removal (CDR) capacity by OAE is also identified. Future work will look to include coastal enhanced weathering of olivine to the portfolio of Spain’s OAE approaches.
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