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Book
Le nouveau voisinage de l'Union européenne élargie
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ISBN: 8387919616 Year: 2004 Publisher: Warszawa : Wyzsza szkola menedzerskka sig,

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Evolutionary Hierarchical Multi-Criteria Metaheuristics for Scheduling in Large-Scale Grid Systems
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ISBN: 9783642289712 Year: 2012 Publisher: Berlin, Heidelberg Imprint: Springer

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Book
High-Performance Modelling and Simulation for Big Data Applications : Selected Results of the COST Action IC1406 cHiPSet
Authors: --- ---
ISBN: 3030162729 3030162710 Year: 2019 Publisher: Cham : Springer International Publishing : Imprint: Springer,

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This open access book is the final compendium of case studies emanated from the 4-year COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications” (cHiPSet). Funded by the European Commission from 2015, cHiPSet has created a sustainable reference network linking applied research in High Performance Computing (HPC) and Modelling & Simulation to tangibly address Big Data challenges. cHiPSet has enabled research partnerships for dozens of academics and industry practitioners located in 34 COST countries, as well as in Australia, Belarus, Brazil, China, Russia, and the USA. As a cooperation framework, cHiPSet has reached out to new audiences such as ICT professionals, commercial software developers, and the general public. At a time when Big Data has become a common household term, cHiPSet has strived to become a knowledge hub where data-driven HPC meets Modelling & Simulation. cHiPSet has also endeavoured to use and exploit results through Open Science practices, i.e., open access publication, open access to data repositories, and open-source software development. A testament to this philosophy, this compendium is set to become a required reference for the fast-changing fields of HPC, Big Data, and Modelling & Simulation.

Keywords

Computer system performance. --- Computer Communication Networks. --- Computer science. --- Logic design. --- Operating systems (Computers). --- System Performance and Evaluation. --- Processor Architectures. --- Information Systems Applications (incl. Internet). --- Logic Design. --- Operating Systems. --- Computer operating systems --- Computers --- Disk operating systems --- Systems software --- Design, Logic --- Design of logic systems --- Digital electronics --- Electronic circuit design --- Logic circuits --- Machine theory --- Switching theory --- Informatics --- Science --- Operating systems --- Computer system failures. --- Computer communication systems. --- Microprocessors. --- Application software. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Minicomputers --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Electronic data processing --- Network computers --- Computer failures --- Computer malfunctions --- Computer systems --- Failure of computer systems --- System failures (Engineering) --- Fault-tolerant computing --- Distributed processing --- Failures --- Computer science --- Computer system failures --- Microprocessors --- Application software --- Logic design --- Operating systems (Computers) --- Electronic digital computers—Evaluation. --- Computer networks. --- Computer architecture. --- Computer and Information Systems Applications. --- Architecture, Computer


Book
Evolutionary Hierarchical Multi-Criteria Metaheuristics for Scheduling in Large-Scale Grid Systems
Authors: ---
ISBN: 9783642289712 Year: 2012 Publisher: Berlin, Heidelberg Springer Berlin Heidelberg

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One of the most challenging issues in modelling today's large-scale computational systems is to effectively manage highly parametrised distributed environments such as computational grids, clouds, ad hoc networks and P2P networks. Next-generation computational grids must provide a wide range of services and high performance computing infrastructures. Various types of information and data processed in the large-scale dynamic grid environment may be incomplete, imprecise, and fragmented, which complicates the specification of proper evaluation criteria and which affects both the availability of resources and the final collective decisions of users. The complexity of grid architectures and grid management may also contribute towards higher energy consumption. All of these issues necessitate the development of intelligent resource management techniques, which are capable of capturing all of this complexity and optimising meaningful metrics for a wide range of grid applications.   This book covers hot topics in the design, administration and management of dynamic grid environments with a special emphasis on the preferences and autonomous decisions of system users, secure access to the processed data and services, and application of green technologies. It features advanced research related to scalable genetic-based heuristic approaches to grid scheduling, whereby new scheduling criteria, such as system reliability, security, and energy consumption are incorporated into a general scheduling model. This book may be a valuable reference for students, researchers, and practitioners who work on - or who are interested in joining -- interdisciplinary research efforts in the areas of distributed and evolutionary computation.  


Book
Intelligent Agents in Data-intensive Computing
Authors: --- ---
ISBN: 3319237411 331923742X Year: 2016 Publisher: Cham : Springer International Publishing : Imprint: Springer,

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This book presents new approaches that advance research in all aspects of agent-based models, technologies, simulations and implementations for data intensive applications. The nine chapters contain a review of recent cross-disciplinary approaches in cloud environments and multi-agent systems, and important formulations of data intensive problems in distributed computational environments together with the presentation of new agent-based tools to handle those problems and Big Data in general. This volume can serve as a reference for students, researchers and industry practitioners working in or interested in joining interdisciplinary work in the areas of data intensive computing and Big Data systems using emergent large-scale distributed computing paradigms. It will also allow newcomers to grasp key concepts and potential solutions on advanced topics of theory, models, technologies, system architectures and implementation of applications in Multi-Agent systems and data intensive computing. .

Keywords

Computer Science --- Engineering & Applied Sciences --- Intelligent agents (Computer software) --- Cloud computing. --- Agents, Autonomous (Computer software) --- Agents, Cognitive (Computer software) --- Agents, Intelligent (Computer software) --- Assistants, Cognitive (Computer software) --- Assistants, Intelligent software --- Autonomous agents (Computer software) --- Cognitive agents (Computer software) --- Cognitive assistants (Computer software) --- IAs (Computer software) --- Intelligent agent software --- Intelligent software agents --- Intelligent software assistants --- Software agents (Computer software) --- Special agents (Computer software) --- Engineering. --- Data mining. --- Artificial intelligence. --- Computational intelligence. --- Computational Intelligence. --- Data Mining and Knowledge Discovery. --- Artificial Intelligence (incl. Robotics). --- Intelligence, Computational --- Artificial intelligence --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Construction --- Industrial arts --- Technology --- Soft computing --- Web services --- Distributed processing --- Computer programs --- Artificial Intelligence.


Book
Modeling and Simulation in HPC and Cloud Systems
Authors: --- ---
ISBN: 3319737678 331973766X Year: 2018 Publisher: Cham : Springer International Publishing : Imprint: Springer,

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This book consists of eight chapters, five of which provide a summary of the tutorials and workshops organised as part of the cHiPSet Summer School: High-Performance Modelling and Simulation for Big Data Applications Cost Action on “New Trends in Modelling and Simulation in HPC Systems,” which was held in Bucharest (Romania) on September 21–23, 2016. As such it offers a solid foundation for the development of new-generation data-intensive intelligent systems. Modelling and simulation (MS) in the big data era is widely considered the essential tool in science and engineering to substantiate the prediction and analysis of complex systems and natural phenomena. MS offers suitable abstractions to manage the complexity of analysing big data in various scientific and engineering domains. Unfortunately, big data problems are not always easily amenable to efficient MS over HPC (high performance computing). Further, MS communities may lack the detailed expertise required to exploit the full potential of HPC solutions, and HPC architects may not be fully aware of specific MS requirements. The main goal of the Summer School was to improve the participants’ practical skills and knowledge of the novel HPC-driven models and technologies for big data applications. The trainers, who are also the authors of this book, explained how to design, construct, and utilise the complex MS tools that capture many of the HPC modelling needs, from scalability to fault tolerance and beyond. In the final three chapters, the book presents the first outcomes of the school: new ideas and novel results of the research on security aspects in clouds, first prototypes of the complex virtual models of data in big data streams and a data-intensive computing framework for opportunistic networks. It is a valuable reference resource for those wanting to start working in HPC and big data systems, as well as for advanced researchers and practitioners. .


Book
Cybersecurity of digital service chains : challenges, methodologies, and tools
Authors: --- ---
ISBN: 3031040368 303104035X Year: 2022 Publisher: Cham : Springer International Publishing AG,

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This open access book presents the main scientific results from the H2020 GUARD project. The GUARD project aims at filling the current technological gap between software management paradigms and cybersecurity models, the latter still lacking orchestration and agility to effectively address the dynamicity of the former. This book provides a comprehensive review of the main concepts, architectures, algorithms, and non-technical aspects developed during three years of investigation; the description of the Smart Mobility use case developed at the end of the project gives a practical example of how the GUARD platform and related technologies can be deployed in practical scenarios. We expect the book to be interesting for the broad group of researchers, engineers, and professionals daily experiencing the inadequacy of outdated cybersecurity models for modern computing environments and cyber-physical systems.


Digital
Intelligent Agents in Data-intensive Computing
Authors: --- ---
ISBN: 9783319237428 Year: 2016 Publisher: Cham Springer International Publishing

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This book presents new approaches that advance research in all aspects of agent-based models, technologies, simulations and implementations for data intensive applications. The nine chapters contain a review of recent cross-disciplinary approaches in cloud environments and multi-agent systems, and important formulations of data intensive problems in distributed computational environments together with the presentation of new agent-based tools to handle those problems and Big Data in general. This volume can serve as a reference for students, researchers and industry practitioners working in or interested in joining interdisciplinary work in the areas of data intensive computing and Big Data systems using emergent large-scale distributed computing paradigms. It will also allow newcomers to grasp key concepts and potential solutions on advanced topics of theory, models, technologies, system architectures and implementation of applications in Multi-Agent systems and data intensive computing. .


Digital
Resource Management for Big Data Platforms : Algorithms, Modelling, and High-Performance Computing Techniques
Authors: --- ---
ISBN: 9783319448817 Year: 2016 Publisher: Cham Springer International Publishing

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This book constitutes a flagship driver towards presenting and supporting advance research in the area of Big Data platforms and applications. Extracting valuable information from raw data is especially difficult considering the velocity of growing data from year to year and the fact that 80% of data is unstructured. In addition, data sources are heterogeneous (various sensors, users with different profiles, etc.) and are located in different situations or contexts. Successful contributions may range from advanced technologies, applications and innovative solutions to global optimization problems in scalable large-scale computing systems to development of methods, conceptual and theoretical models related to Big Data applications and massive data storage and processing. The book provides, in this sense, a platform for the dissemination of advanced topics of theory, research efforts and analysis and implementation for Big Data platforms and applications being oriented on methods, techniques and performance evaluation. This book presents new ideas, analysis, implementations and evaluation of next-generation Big Data platforms and applications. In 23 chapters, several important formulations of the architecture design, optimization techniques, advanced analytics methods, biological, medical and social media applications are presented. These subjects represent the main objectives of ICT COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications (cHiPSet) and the research presented in these chapters was performed by joint collaboration of members from this action. This volume will serve as a reference for students, researchers and industry practitioners working in or interested in joining interdisciplinary works in the areas of intelligent decision systems using emergent distributed computing paradigms. It will also allow newcomers to grasp the key concerns and potential solutions for the selected topics.


Digital
Modeling and Simulation in HPC and Cloud Systems
Authors: --- ---
ISBN: 9783319737676 Year: 2018 Publisher: Cham Springer International Publishing

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Abstract

This book consists of eight chapters, five of which provide a summary of the tutorials and workshops organised as part of the cHiPSet Summer School: High-Performance Modelling and Simulation for Big Data Applications Cost Action on “New Trends in Modelling and Simulation in HPC Systems,” which was held in Bucharest (Romania) on September 21–23, 2016. As such it offers a solid foundation for the development of new-generation data-intensive intelligent systems. Modelling and simulation (MS) in the big data era is widely considered the essential tool in science and engineering to substantiate the prediction and analysis of complex systems and natural phenomena. MS offers suitable abstractions to manage the complexity of analysing big data in various scientific and engineering domains. Unfortunately, big data problems are not always easily amenable to efficient MS over HPC (high performance computing). Further, MS communities may lack the detailed expertise required to exploit the full potential of HPC solutions, and HPC architects may not be fully aware of specific MS requirements. The main goal of the Summer School was to improve the participants’ practical skills and knowledge of the novel HPC-driven models and technologies for big data applications. The trainers, who are also the authors of this book, explained how to design, construct, and utilise the complex MS tools that capture many of the HPC modelling needs, from scalability to fault tolerance and beyond. In the final three chapters, the book presents the first outcomes of the school: new ideas and novel results of the research on security aspects in clouds, first prototypes of the complex virtual models of data in big data streams and a data-intensive computing framework for opportunistic networks. It is a valuable reference resource for those wanting to start working in HPC and big data systems, as well as for advanced researchers and practitioners. .

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