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Fast and Scalable Cloud Data Management, Gessert Felix, Wingerath Wolfram, Ritter Norbert
Gessert Felix, Wingerath Wolfram, Ritter Norbert Fast and Scalable Cloud Data Management 9783030435059

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Цена: 19564.00р.
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Автор: Gessert Felix, Wingerath Wolfram, Ritter Norbert
Название:  Fast and Scalable Cloud Data Management
ISBN: 9783030435059
Издательство: Springer
Классификация:
Сетевое оборудование

Базы данных

Информационный поиск

ISBN-10: 3030435059
Обложка/Формат: Hardcover
Страницы: 193
Вес: 0.47 кг.
Дата издания: 16.05.2020
Язык: English
Издание: 1st ed. 2020
Иллюстрации: 17 illustrations, color; 14 illustrations, black and white; xi, 193 p. 31 illus., 17 illus. in color.
Размер: 23.39 x 15.60 x 1.27 cm
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Preface.- 1 Introduction.- 2 Latency in Cloud-Based Applications.- 3 HTTP for Globally Distributed Applications.- 4 Systems for Scalable Data Management.- 5 Caching in Research & Industry.- 6 Transactional Semantics.-7 Polyglot Persistence in Data Management.- 8 The NoSQL Toolbox: The NoSQL Landscape in a Nutshell.- 9 Summary & Future Trends.


Software Project Management for Distributed Computing: Life-Cycle Methods for Developing Scalable and Reliable Tools

Автор: Mahmood Zaigham
Название: Software Project Management for Distributed Computing: Life-Cycle Methods for Developing Scalable and Reliable Tools
ISBN: 3319853708 ISBN-13(EAN): 9783319853703
Издательство: Springer
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Цена: 13974.00 р.
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Описание:

Part I: Characteristics and Estimation of Software Projects for Distributed Computing

Modelling of Reusability Estimation in Software Design with External Constraints
R. Selvarani and P. Mangayarkarasi

Estimation of Costs and Time for the Development of Distributed Software
Manal El Bajta, Ali Idri, Joaquнn Nicolas Ros, Josй Luis Fernandez-Aleman, and Ambrosio Toval

Using COSMIC for the Functional Size Measurement of Distributed Applications in Cloud Environments
Filomena Ferrucci, Carmine Gravino, and Pasquale Salza

Characteristics of Large-Scale Defense Projects and the Dominance of Software and Software Project Management
Kadir Alpaslan Demir

Software Project Management as a Service (SPMaaS): Perspectives and Benefits
Muthu Ramachandran and Vikrant Chaugule

Part II: Approached and Frameworks for Software Development and Software Project Management

Component-Based Hybrid Reference Architecture for Managing Adaptable Embedded Software Development
Bo Xing

3PR Framework for Software Project Management: People, Processes, Products and Risks
Kadir Alpaslan Demir

CrowdSWD: A Novel Framework for Crowdsourcing Software Development Inspired by the Concept of Biological Metaphor
Tarek A. Ali, Eman S. Nasr, and Mervat H. Gheith

An Approach to Migrate and Manage Software: Cloud Based Requirements Management
Areeg Samir

A Novel Approach to Modelling Distributed Systems - Using Large-Scale Multi-Agent Systems
Bogdan Okresa Đuric

Part III: Advances in Software Project Management and Distributed Software Development

Optimizing Software Error Proneness Prediction using Bird Mating AlgorithmAmrit Pal, Harsh Jain, and Manish Kumar

i(mproved)Agile: A Customized Scrum Process for Project Management in Defense & Security
Luigi Benedicenti, Paolo Ciancarini, Franco Cotugno, Angelo Messina, Alberto Sillitti, and Giancarlo Succi

Ontology Annotation for Software Engineering Project Management in Multi-site Distributed Software Development Environments
Pornpit Wongthongtham, Udsanee Pakdeetrakulwong, and Syed Hassan Marzooq

Investigating the Scope for Agile Project Management to be Adopted by Higher Education Institutions
Simon P Philbin

Software Project Management for Combined Software and Data Engineering
Seyyed M. Shah, James Welch, Jim Davies, and Jeremy Gibbons
Ceph: Designing and Implementing Scalable Storage Systems

Автор: Hackett Michael, Umrao Vikhyat, Singh Karan
Название: Ceph: Designing and Implementing Scalable Storage Systems
ISBN: 1788295412 ISBN-13(EAN): 9781788295413
Издательство: Неизвестно
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Цена: 9194.00 р.
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Описание: Ceph is an open source storage solution that runs on commodity hardware and provides exabyte-level scalability. With this Learning Path, you can become an expert in the most advanced features of Ceph and design, implement, and manage a highly reliable storage system that has no single point of failure.

Professional Azure SQL Managed Database Administration - Third Edition: Efficiently manage and modernize data in the cloud using Azure SQL

Автор: Osama Ahmad
Название: Professional Azure SQL Managed Database Administration - Third Edition: Efficiently manage and modernize data in the cloud using Azure SQL
ISBN: 1801076529 ISBN-13(EAN): 9781801076524
Издательство: Неизвестно
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Цена: 10114.00 р.
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Описание: Whether it is learning different techniques to monitor and tune an Azure SQL database or improving performance using in-memory technology, this book will enable you to make the most out of Azure SQL database features and functionality for data management solutions.

Engineering Scalable, Elastic, and Cost-Efficient Cloud Computing Applications: The Cloudscale Method

Автор: Becker Steffen, Brataas Gunnar, Lehrig Sebastian
Название: Engineering Scalable, Elastic, and Cost-Efficient Cloud Computing Applications: The Cloudscale Method
ISBN: 3319853635 ISBN-13(EAN): 9783319853635
Издательство: Springer
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Цена: 7685.00 р.
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Описание: This book provides an overview of the problems involved in engineering scalable, elastic, and cost-efficient cloud computing services and describes the CloudScale method - a description of rescuing tools and the required steps to exploit these tools.

Engineering scalable, elastic, and cost-efficient cloud computing applications

Название: Engineering scalable, elastic, and cost-efficient cloud computing applications
ISBN: 3319542850 ISBN-13(EAN): 9783319542850
Издательство: Springer
Рейтинг:
Цена: 7685.00 р.
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Описание: Overviewing problems involved in engineering scalable, elastic, and cost-efficient cloud computing services, this book describes the CloudScale method a description of rescuing tools and the required steps to exploit these tools. With the CloudScale method, software architects can analyze both existing and planned IT services.

Scalable Big Data Analytics for Protein Bioinformatics

Автор: Dariusz Mrozek
Название: Scalable Big Data Analytics for Protein Bioinformatics
ISBN: 3030075389 ISBN-13(EAN): 9783030075385
Издательство: Springer
Рейтинг:
Цена: 13974.00 р.
Наличие на складе: Поставка под заказ.

Описание:

This book presents a focus on proteins and their structures. The text describes various scalable solutions for protein structure similarity searching, carried out at main representation levels and for prediction of 3D structures of proteins. Emphasis is placed on techniques that can be used to accelerate similarity searches and protein structure modeling processes.
The content of the book is divided into four parts. The first part provides background information on proteins and their representation levels, including a formal model of a 3D protein structure used in computational processes, and a brief overview of the technologies used in the solutions presented in the book. The second part of the book discusses Cloud services that are utilized in the development of scalable and reliable cloud applications for 3D protein structure similarity searching and protein structure prediction. The third part of the book shows the utilization of scalable Big Data computational frameworks, like Hadoop and Spark, in massive 3D protein structure alignments and identification of intrinsically disordered regions in protein structures. The fourth part of the book focuses on finding 3D protein structure similarities, accelerated with the use of GPUs and the use of multithreading and relational databases for efficient approximate searching on protein secondary structures.
The book introduces advanced techniques and computational architectures that benefit from recent achievements in the field of computing and parallelism. Recent developments in computer science have allowed algorithms previously considered too time-consuming to now be efficiently used for applications in bioinformatics and the life sciences. Given its depth of coverage, the book will be of interest to researchers and software developers working in the fields of structural bioinformatics and biomedical databases.
Scalable Big Data Analytics for Protein Bioinformatics

Автор: Dariusz Mrozek
Название: Scalable Big Data Analytics for Protein Bioinformatics
ISBN: 3319988387 ISBN-13(EAN): 9783319988382
Издательство: Springer
Рейтинг:
Цена: 13974.00 р.
Наличие на складе: Поставка под заказ.

Описание:

This book presents a focus on proteins and their structures. The text describes various scalable solutions for protein structure similarity searching, carried out at main representation levels and for prediction of 3D structures of proteins. Emphasis is placed on techniques that can be used to accelerate similarity searches and protein structure modeling processes.
The content of the book is divided into four parts. The first part provides background information on proteins and their representation levels, including a formal model of a 3D protein structure used in computational processes, and a brief overview of the technologies used in the solutions presented in the book. The second part of the book discusses Cloud services that are utilized in the development of scalable and reliable cloud applications for 3D protein structure similarity searching and protein structure prediction. The third part of the book shows the utilization of scalable Big Data computational frameworks, like Hadoop and Spark, in massive 3D protein structure alignments and identification of intrinsically disordered regions in protein structures. The fourth part of the book focuses on finding 3D protein structure similarities, accelerated with the use of GPUs and the use of multithreading and relational databases for efficient approximate searching on protein secondary structures.
The book introduces advanced techniques and computational architectures that benefit from recent achievements in the field of computing and parallelism. Recent developments in computer science have allowed algorithms previously considered too time-consuming to now be efficiently used for applications in bioinformatics and the life sciences. Given its depth of coverage, the book will be of interest to researchers and software developers working in the fields of structural bioinformatics and biomedical databases.
Scalable Network Monitoring in High Speed Networks

Автор: Baek-Young Choi; Zhi-Li Zhang; David Hung-Chang Du
Название: Scalable Network Monitoring in High Speed Networks
ISBN: 1489985638 ISBN-13(EAN): 9781489985637
Издательство: Springer
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Цена: 12577.00 р.
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Описание: Network monitoring serves as the basis for a wide scope of network, engineering and management operations. This book presents accurate measurement schemes from both traffic and performance perspectives, and introduces some adaptive sampling techniques.

Building Scalable Network Services

Автор: Cheng Jin; Sugih Jamin; Danny Raz; Yuval Shavitt
Название: Building Scalable Network Services
ISBN: 1461347114 ISBN-13(EAN): 9781461347118
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Building Scalable Network Services: Theory and Practice is on building scalable network services on the Internet or in a network service provider`s network.

Scalable Uncertainty Management: 14th International Conference, Sum 2020, Bozen-Bolzano, Italy, September 23-25, 2020, Proceedings

Автор: Davis Jesse, Tabia Karim
Название: Scalable Uncertainty Management: 14th International Conference, Sum 2020, Bozen-Bolzano, Italy, September 23-25, 2020, Proceedings
ISBN: 3030584488 ISBN-13(EAN): 9783030584481
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This book constitutes the refereed proceedings of the 14th International Conference on Scalable Uncertainty Management, SUM 2020, which was held in Bozen-Bolzano, Italy, in September 2020. The 12 full, 7 short papers presented in this volume were carefully reviewed and selected from 30 submissions.

Scalable Uncertainty Management

Автор: Schockaert
Название: Scalable Uncertainty Management
ISBN: 3319458558 ISBN-13(EAN): 9783319458557
Издательство: Springer
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Цена: 8106.00 р.
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Описание: Combinatorial Games: From Theoretical Solving to AI Algorithms.- A Gentle Introduction to Reinforcement Learning.- Possibilistic Graphical Models for Uncertainty Modeling.- On the Explanation of SameAs Statements using Argumentation.- Reasoning with Multiple-Agent Possibilistic Logic.- Incremental Preference Elicitation in Multi-Attribute Domains for Choice and Ranking with the Borda Count.- Graphical Models for Preference Representation: An Overview.- Diffusion of Opinion and Influence.- Fuzzy Labeling for Abstract Argumentation: An Empirical Evaluation.- A Belief-Based Approach to Measuring Message Acceptability.- Intertranslatability of Labeling-based Argumentation Semantics.- Preference Inference Based on Pareto Models.- Persuasion Dialogues via Restricted Interfaces using Probabilistic Argumentation.- Metric Logic Program Explanations for Complex Separator Functions.- A Two-Stage Online Approach for Collaborative Multi-Agent Planning under Uncertainty.- 9-ASP for Computing Repairs with Existential Ontologies.- Probabilistic Reasoning in the Description Logic ALCP with the Principle of Maximum Entropy.- Fuzzy Quantified Structural Queries to Fuzzy Graph Databases.- Reasoning with Data - A New Challenge For AI.- Probabilistic Spatial Reasoning in Constraint Logic Programming.- ChoiceGAPs: Competitive Diffusion as a Massive Multi-Player Game in Social Networks.- Challenges for Efficient Query Evaluation on Structured Probabilistic Data.- Forgetting-Based Inconsistency Measure.- A Possibilistic Multivariate Fuzzy c-Means Clustering Algorithm.- A Measure of Referential Success Based on Alpha-Cuts.- Graded Justification of Arguments via Internal and External Endogenous Features.

Scalable Uncertainty Management

Автор: Christoph Beierle; Alex Dekhtyar
Название: Scalable Uncertainty Management
ISBN: 3319235397 ISBN-13(EAN): 9783319235394
Издательство: Springer
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Цена: 8944.00 р.
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Описание:

The mysterious world of normal numbers.- Bayesian Networks.- Probabilistic Query Answering in the Bayesian Description Logic BEL.- The Complexity of Plate Probabilistic Models.- DL-Lite Bayesian Networks: A Tractable Probabilistic Graphical Model.- Probabilistic Models.- State Space Search with Stochastic Costs and Risk Aversion.- On the Impact of Junction-Tree Topology on Weighted Model Counting.- A System for Probabilistic Inductive Answer Set Programming.- Towards Large-Scale Probabilistic OBDA.- Reasoning over Linear Probabilistic Knowledge Bases with Priorities.- Intelligent Data Analytics.- Evenness-based reasoning with logical proportions applied to classification.- Multivariate Cluster-Based Discretization for Bayesian Network Structure Learning.- Modeling and Forecasting Time Series of Compositional Data: A Generalized Dirichlet Power Steady Model.- Linguistic and Graphical Explanation of a Cluster-based Data Structure.- Possibility Theory, Belief Functions and Transformations.- Probability-possibility transformations: Application to credal networks.- Planning in Partially Observable Domains with Fuzzy Epistemic States and Probabilistic Dynamics.- Propagation of Belief Functions in Singly-Connected Hybrid Directed Evidential Networks.- Uncertain logical gates in possibilistic networks. An application to human geography.- Argumentation.- Undercutting in argumentation systems.- Formalizing Explanatory Dialogues.- Towards a dual process cognitive model for argument evaluation.- Change in abstract bipolar argumentation systems.- On argumentation with purely defeasible rules.- Dealing with Inconsistency.- A possibilistic analysis of inconsistency.- First-Order Under-Approximations of Consistent Query Answers.- Using Rules of Thumb for Repairing Inconsistent Answer Set Program.- Applications.- Fuzzy XPath for the Automatic Search of Fuzzy Formulae Models.- ERBlox: Combining Matching Dependencies with Machine Learning for Entity Resolution.- Matching uncertain identities against sparse knowledge.


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