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Author : Hilmi Egemen Ciritoglu
Publisher :
ISBN 13 :
Total Pages : 132 pages
Book Rating : 4.:/5 (129 download)
Download or read book Replication Management for Large-scale Data-intensive Clusters written by Hilmi Egemen Ciritoglu and published by . This book was released on 2021 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Aziz Gul̈beden
Publisher :
ISBN 13 :
Total Pages : 86 pages
Book Rating : 4.:/5 (584 download)
Download or read book Replication Management in Self-organizing Clusters for Parallel Data-intensive Applications written by Aziz Gul̈beden and published by . This book was released on 2004 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Kosar, Tevfik
Publisher : IGI Global
ISBN 13 : 1615209727
Total Pages : 353 pages
Book Rating : 4.6/5 (152 download)
Download or read book Data Intensive Distributed Computing: Challenges and Solutions for Large-scale Information Management written by Kosar, Tevfik and published by IGI Global. This book was released on 2012-01-31 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book focuses on the challenges of distributed systems imposed by the data intensive applications, and on the different state-of-the-art solutions proposed to overcome these challenges"--Provided by publisher.
Author : Noha Adly
Publisher :
ISBN 13 :
Total Pages : 208 pages
Book Rating : 4.:/5 (321 download)
Download or read book Management of Replicated Data in Large Scale Systems written by Noha Adly and published by . This book was released on 1995 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Daniel C. M. de Oliveira
Publisher : Morgan & Claypool Publishers
ISBN 13 : 168173558X
Total Pages : 181 pages
Book Rating : 4.6/5 (817 download)
Download or read book Data-Intensive Workflow Management written by Daniel C. M. de Oliveira and published by Morgan & Claypool Publishers. This book was released on 2019-05-13 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: Workflows may be defined as abstractions used to model the coherent flow of activities in the context of an in silico scientific experiment. They are employed in many domains of science such as bioinformatics, astronomy, and engineering. Such workflows usually present a considerable number of activities and activations (i.e., tasks associated with activities) and may need a long time for execution. Due to the continuous need to store and process data efficiently (making them data-intensive workflows), high-performance computing environments allied to parallelization techniques are used to run these workflows. At the beginning of the 2010s, cloud technologies emerged as a promising environment to run scientific workflows. By using clouds, scientists have expanded beyond single parallel computers to hundreds or even thousands of virtual machines. More recently, Data-Intensive Scalable Computing (DISC) frameworks (e.g., Apache Spark and Hadoop) and environments emerged and are being used to execute data-intensive workflows. DISC environments are composed of processors and disks in large-commodity computing clusters connected using high-speed communications switches and networks. The main advantage of DISC frameworks is that they support and grant efficient in-memory data management for large-scale applications, such as data-intensive workflows. However, the execution of workflows in cloud and DISC environments raise many challenges such as scheduling workflow activities and activations, managing produced data, collecting provenance data, etc. Several existing approaches deal with the challenges mentioned earlier. This way, there is a real need for understanding how to manage these workflows and various big data platforms that have been developed and introduced. As such, this book can help researchers understand how linking workflow management with Data-Intensive Scalable Computing can help in understanding and analyzing scientific big data. In this book, we aim to identify and distill the body of work on workflow management in clouds and DISC environments. We start by discussing the basic principles of data-intensive scientific workflows. Next, we present two workflows that are executed in a single site and multi-site clouds taking advantage of provenance. Afterward, we go towards workflow management in DISC environments, and we present, in detail, solutions that enable the optimized execution of the workflow using frameworks such as Apache Spark and its extensions.
Author : Terence Critchlow
Publisher : CRC Press
ISBN 13 : 100075569X
Total Pages : 449 pages
Book Rating : 4.0/5 (7 download)
Download or read book Data-Intensive Science written by Terence Critchlow and published by CRC Press. This book was released on 2016-04-19 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-intensive science has the potential to transform scientific research and quickly translate scientific progress into complete solutions, policies, and economic success. But this collaborative science is still lacking the effective access and exchange of knowledge among scientists, researchers, and policy makers across a range of disciplines. Bringing together leaders from multiple scientific disciplines, Data-Intensive Science shows how a comprehensive integration of various techniques and technological advances can effectively harness the vast amount of data being generated and significantly accelerate scientific progress to address some of the world's most challenging problems. In the book, a diverse cross-section of application, computer, and data scientists explores the impact of data-intensive science on current research and describes emerging technologies that will enable future scientific breakthroughs. The book identifies best practices used to tackle challenges facing data-intensive science as well as gaps in these approaches. It also focuses on the integration of data-intensive science into standard research practice, explaining how components in the data-intensive science environment need to work together to provide the necessary infrastructure for community-scale scientific collaborations. Organizing the material based on a high-level, data-intensive science workflow, this book provides an understanding of the scientific problems that would benefit from collaborative research, the current capabilities of data-intensive science, and the solutions to enable the next round of scientific advancements.
Author : L. Grandinetti
Publisher : IOS Press
ISBN 13 : 1614998825
Total Pages : 338 pages
Book Rating : 4.6/5 (149 download)
Download or read book Big Data and HPC: Ecosystem and Convergence written by L. Grandinetti and published by IOS Press. This book was released on 2018-08-22 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the increasing need to solve complex problems, high-performance computing (HPC) is now one of the most fundamental infrastructures for scientific development in all disciplines, and it has progressed massively in recent years as a result. HPC facilitates the processing of big data, but the tremendous research challenges faced in recent years include: the scalability of computing performance for high velocity, high variety and high volume big data; deep learning with massive-scale datasets; big data programming paradigms on multi-core; GPU and hybrid distributed environments; and unstructured data processing with high-performance computing. This book presents 19 selected papers from the TopHPC2017 congress on Advances in High-Performance Computing and Big Data Analytics in the Exascale era, held in Tehran, Iran, in April 2017. The book is divided into 3 sections: State of the Art and Future Scenarios, Big Data Challenges, and HPC Challenges, and will be of interest to all those whose work involves the processing of Big Data and the use of HPC.
Author : Jad Darrous
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (114 download)
Download or read book Scalable and Efficient Data Management in Distributed Clouds written by Jad Darrous and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis focuses on scalable data management solutions to accelerate service provisioning and enable efficient execution of data-intensive applications in large-scale distributed clouds. Data-intensive applications are increasingly running on distributed infrastructures (multiple clusters). The main two reasons for such a trend are 1) moving computation to data sources can eliminate the latency of data transmission, and 2) storing data on one site may not be feasible given the continuous increase of data size.On the one hand, most applications run on virtual clusters to provide isolated services, and require virtual machine images (VMIs) or container images to provision such services. Hence, it is important to enable fast provisioning of virtualization services to reduce the waiting time of new running services or applications. Different from previous work, during the first part of this thesis, we worked on optimizing data retrieval and placement considering challenging issues including the continuous increase of the number and size of VMIs and container images, and the limited bandwidth and heterogeneity of the wide area network (WAN) connections.On the other hand, data-intensive applications rely on replication to provide dependable and fast services, but it became expensive and even infeasible with the unprecedented growth of data size. The second part of this thesis provides one of the first studies on understanding and improving the performance of data-intensive applications when replacing replication with the storage-efficient erasure coding (EC) technique.
Author : Jeng-Shyang Pan
Publisher : Springer Science & Business Media
ISBN 13 : 3642284892
Total Pages : 593 pages
Book Rating : 4.6/5 (422 download)
Download or read book Intelligent Information and Database Systems written by Jeng-Shyang Pan and published by Springer Science & Business Media. This book was released on 2012-03-02 with total page 593 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNAI 7196, LNAI 7197 and LNAI 7198 constitutes the refereed proceedings of the 4th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2012, held in Kaohsiung, Taiwan in March 2012. The 161 revised papers presented were carefully reviewed and selected from more than 472 submissions. The papers included cover the following topics: intelligent database systems, data warehouses and data mining, natural language processing and computational linguistics, semantic Web, social networks and recommendation systems, collaborative systems and applications, e-bussiness and e-commerce systems, e-learning systems, information modeling and requirements engineering, information retrieval systems, intelligent agents and multi-agent systems, intelligent information systems, intelligent internet systems, intelligent optimization techniques, object-relational DBMS, ontologies and knowledge sharing, semi-structured and XML database systems, unified modeling language and unified processes, Web services and semantic Web, computer networks and communication systems.
Author : Kyriazis, Dimosthenis
Publisher : IGI Global
ISBN 13 : 1466639350
Total Pages : 342 pages
Book Rating : 4.4/5 (666 download)
Download or read book Data Intensive Storage Services for Cloud Environments written by Kyriazis, Dimosthenis and published by IGI Global. This book was released on 2013-04-30 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the evolution of digitized data, our society has become dependent on services to extract valuable information and enhance decision making by individuals, businesses, and government in all aspects of life. Therefore, emerging cloud-based infrastructures for storage have been widely thought of as the next generation solution for the reliance on data increases. Data Intensive Storage Services for Cloud Environments provides an overview of the current and potential approaches towards data storage services and its relationship to cloud environments. This reference source brings together research on storage technologies in cloud environments and various disciplines useful for both professionals and researchers.
Author : Emilio Luque
Publisher : Springer
ISBN 13 : 3540854517
Total Pages : 991 pages
Book Rating : 4.5/5 (48 download)
Download or read book Euro-Par 2008 Parallel Processing written by Emilio Luque and published by Springer. This book was released on 2008-08-21 with total page 991 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 14th International Conference on Parallel Computing, Euro-Par 2008, held in Las Palmas de Gran Canaria, Spain, in August 2008. The 86 revised papers presented were carefully reviewed and selected from 264 submissions. The papers are organized in topical sections on support tools and environments; performance prediction and evaluation; scheduling and load balancing; high performance architectures and compilers; parallel and distributed databases; grid and cluster computing; peer-to-peer computing; distributed systems and algorithms; parallel and distributed programming; parallel numerical algorithms; distributed and high-performance multimedia; theory and algorithms for parallel computation; and high performance networks.
Author : Ivan Mistrik
Publisher : Morgan Kaufmann
ISBN 13 : 0128093382
Total Pages : 472 pages
Book Rating : 4.1/5 (28 download)
Download or read book Software Architecture for Big Data and the Cloud written by Ivan Mistrik and published by Morgan Kaufmann. This book was released on 2017-06-12 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Software Architecture for Big Data and the Cloud is designed to be a single resource that brings together research on how software architectures can solve the challenges imposed by building big data software systems. The challenges of big data on the software architecture can relate to scale, security, integrity, performance, concurrency, parallelism, and dependability, amongst others. Big data handling requires rethinking architectural solutions to meet functional and non-functional requirements related to volume, variety and velocity. The book's editors have varied and complementary backgrounds in requirements and architecture, specifically in software architectures for cloud and big data, as well as expertise in software engineering for cloud and big data. This book brings together work across different disciplines in software engineering, including work expanded from conference tracks and workshops led by the editors. Discusses systematic and disciplined approaches to building software architectures for cloud and big data with state-of-the-art methods and techniques Presents case studies involving enterprise, business, and government service deployment of big data applications Shares guidance on theory, frameworks, methodologies, and architecture for cloud and big data
Author : M. Mittal
Publisher : IOS Press
ISBN 13 : 1614998140
Total Pages : 618 pages
Book Rating : 4.6/5 (149 download)
Download or read book Data Intensive Computing Applications for Big Data written by M. Mittal and published by IOS Press. This book was released on 2018-01-31 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book ‘Data Intensive Computing Applications for Big Data’ discusses the technical concepts of big data, data intensive computing through machine learning, soft computing and parallel computing paradigms. It brings together researchers to report their latest results or progress in the development of the above mentioned areas. Since there are few books on this specific subject, the editors aim to provide a common platform for researchers working in this area to exhibit their novel findings. The book is intended as a reference work for advanced undergraduates and graduate students, as well as multidisciplinary, interdisciplinary and transdisciplinary research workers and scientists on the subjects of big data and cloud/parallel and distributed computing, and explains didactically many of the core concepts of these approaches for practical applications. It is organized into 24 chapters providing a comprehensive overview of big data analysis using parallel computing and addresses the complete data science workflow in the cloud, as well as dealing with privacy issues and the challenges faced in a data-intensive cloud computing environment. The book explores both fundamental and high-level concepts, and will serve as a manual for those in the industry, while also helping beginners to understand the basic and advanced aspects of big data and cloud computing.
Author : M. Tamer Özsu
Publisher : Springer Nature
ISBN 13 : 3030262537
Total Pages : 674 pages
Book Rating : 4.0/5 (32 download)
Download or read book Principles of Distributed Database Systems written by M. Tamer Özsu and published by Springer Nature. This book was released on 2019-12-02 with total page 674 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fourth edition of this classic textbook provides major updates. This edition has completely new chapters on Big Data Platforms (distributed storage systems, MapReduce, Spark, data stream processing, graph analytics) and on NoSQL, NewSQL and polystore systems. It also includes an updated web data management chapter that includes RDF and semantic web discussion, an integrated database integration chapter focusing both on schema integration and querying over these systems. The peer-to-peer computing chapter has been updated with a discussion of blockchains. The chapters that describe classical distributed and parallel database technology have all been updated. The new edition covers the breadth and depth of the field from a modern viewpoint. Graduate students, as well as senior undergraduate students studying computer science and other related fields will use this book as a primary textbook. Researchers working in computer science will also find this textbook useful. This textbook has a companion web site that includes background information on relational database fundamentals, query processing, transaction management, and computer networks for those who might need this background. The web site also includes all the figures and presentation slides as well as solutions to exercises (restricted to instructors).
Author : Daniel Oliveira
Publisher : Springer Nature
ISBN 13 : 3031018729
Total Pages : 161 pages
Book Rating : 4.0/5 (31 download)
Download or read book Data-Intensive Workflow Management written by Daniel Oliveira and published by Springer Nature. This book was released on 2022-06-01 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Workflows may be defined as abstractions used to model the coherent flow of activities in the context of an in silico scientific experiment. They are employed in many domains of science such as bioinformatics, astronomy, and engineering. Such workflows usually present a considerable number of activities and activations (i.e., tasks associated with activities) and may need a long time for execution. Due to the continuous need to store and process data efficiently (making them data-intensive workflows), high-performance computing environments allied to parallelization techniques are used to run these workflows. At the beginning of the 2010s, cloud technologies emerged as a promising environment to run scientific workflows. By using clouds, scientists have expanded beyond single parallel computers to hundreds or even thousands of virtual machines. More recently, Data-Intensive Scalable Computing (DISC) frameworks (e.g., Apache Spark and Hadoop) and environments emerged and are being used to execute data-intensive workflows. DISC environments are composed of processors and disks in large-commodity computing clusters connected using high-speed communications switches and networks. The main advantage of DISC frameworks is that they support and grant efficient in-memory data management for large-scale applications, such as data-intensive workflows. However, the execution of workflows in cloud and DISC environments raise many challenges such as scheduling workflow activities and activations, managing produced data, collecting provenance data, etc. Several existing approaches deal with the challenges mentioned earlier. This way, there is a real need for understanding how to manage these workflows and various big data platforms that have been developed and introduced. As such, this book can help researchers understand how linking workflow management with Data-Intensive Scalable Computing can help in understanding and analyzing scientific big data. In this book, we aim to identify and distill the body of work on workflow management in clouds and DISC environments. We start by discussing the basic principles of data-intensive scientific workflows. Next, we present two workflows that are executed in a single site and multi-site clouds taking advantage of provenance. Afterward, we go towards workflow management in DISC environments, and we present, in detail, solutions that enable the optimized execution of the workflow using frameworks such as Apache Spark and its extensions.
Author : Roy H. Campbell
Publisher : John Wiley & Sons
ISBN 13 : 1119428505
Total Pages : 364 pages
Book Rating : 4.1/5 (194 download)
Download or read book Assured Cloud Computing written by Roy H. Campbell and published by John Wiley & Sons. This book was released on 2018-08-06 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explores key challenges and solutions to assured cloud computing today and provides a provocative look at the face of cloud computing tomorrow This book offers readers a comprehensive suite of solutions for resolving many of the key challenges to achieving high levels of assurance in cloud computing. The distillation of critical research findings generated by the Assured Cloud Computing Center of Excellence (ACC-UCoE) of the University of Illinois, Urbana-Champaign, it provides unique insights into the current and future shape of robust, dependable, and secure cloud-based computing and data cyberinfrastructures. A survivable and distributed cloud-computing-based infrastructure can enable the configuration of any dynamic systems-of-systems that contain both trusted and partially trusted resources and services sourced from multiple organizations. To assure mission-critical computations and workflows that rely on such systems-of-systems it is necessary to ensure that a given configuration does not violate any security or reliability requirements. Furthermore, it is necessary to model the trustworthiness of a workflow or computation fulfillment to a high level of assurance. In presenting the substance of the work done by the ACC-UCoE, this book provides a vision for assured cloud computing illustrating how individual research contributions relate to each other and to the big picture of assured cloud computing. In addition, the book: Explores dominant themes in cloud-based systems, including design correctness, support for big data and analytics, monitoring and detection, network considerations, and performance Synthesizes heavily cited earlier work on topics such as DARE, trust mechanisms, and elastic graphs, as well as newer research findings on topics, including R-Storm, and RAMP transactions Addresses assured cloud computing concerns such as game theory, stream processing, storage, algorithms, workflow, scheduling, access control, formal analysis of safety, and streaming Bringing together the freshest thinking and applications in one of today’s most important topics, Assured Cloud Computing is a must-read for researchers and professionals in the fields of computer science and engineering, especially those working within industrial, military, and governmental contexts. It is also a valuable reference for advanced students of computer science.
Author : Cristea, Valentin
Publisher : IGI Global
ISBN 13 : 161520704X
Total Pages : 276 pages
Book Rating : 4.6/5 (152 download)
Download or read book Large-Scale Distributed Computing and Applications: Models and Trends written by Cristea, Valentin and published by IGI Global. This book was released on 2010-05-31 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many applications follow the distributed computing paradigm, in which parts of the application are executed on different network-interconnected computers. The extension of these applications in terms of number of users or size has led to an unprecedented increase in the scale of the infrastructure that supports them. Large-Scale Distributed Computing and Applications: Models and Trends offers a coherent and realistic image of today's research results in large scale distributed systems, explains state-of-the-art technological solutions for the main issues regarding large scale distributed systems, and presents the benefits of using large scale distributed systems and the development process of scientific and commercial distributed applications.
