Download or read book Data Processing and Workflow Scheduling in Cluster Computing Systems written by Srinath Shankar and published by . This book was released on 2008 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Workflow Scheduling on Computing Systems written by Kenli Li and published by CRC Press. This book was released on 2022-08-12 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will serve as a guide in understanding workflow scheduling techniques on computing systems such as Cluster, Supercomputers, Grid computing, Cloud computing, Edge computing, Fog computing, and the practical realization of such methods. It offers a whole new perspective and holistic approach in understanding computing systems’ workflow scheduling. Expressing and exposing approaches for various process-centric cloud-based applications give a full coverage of most systems’ energy consumption, reliability, resource utilization, cost, and application stochastic computation. By combining theory with application and connecting mathematical concepts and models with their resource management targets, this book will be equally accessible to readers with both Computer Science and Engineering backgrounds. It will be of great interest to students and professionals alike in the field of computing system design, management, and application. This book will also be beneficial to the general audience and technology enthusiasts who want to expand their knowledge on computer structure.

Download or read book Scheduling in Distributed Computing Systems written by Deo Prakash Vidyarthi and published by Springer Science & Business Media. This book was released on 2008-10-20 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book intends to inculcate the innovative ideas for the scheduling aspect in distributed computing systems. Although the models in this book have been designed for distributed systems, the same information is applicable for any type of system. The book will dramatically improve the design and management of the processes for industry professionals. It deals exclusively with the scheduling aspect, which finds little space in other distributed operating system books. Structured for a professional audience composed of researchers and practitioners in industry, this book is also suitable as a reference for graduate-level students.

Download or read book Workflow Scheduling on Computing Systems written by Kenli Li and published by CRC Press. This book was released on 2022-08-12 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will serve as a guide in understanding workflow scheduling techniques on computing systems such as Cluster, Supercomputers, Grid computing, Cloud computing, Edge computing, Fog computing, and the practical realization of such methods. It offers a whole new perspective and holistic approach in understanding computing systems’ workflow scheduling. Expressing and exposing approaches for various process-centric cloud-based applications give a full coverage of most systems’ energy consumption, reliability, resource utilization, cost, and application stochastic computation. By combining theory with application and connecting mathematical concepts and models with their resource management targets, this book will be equally accessible to readers with both Computer Science and Engineering backgrounds. It will be of great interest to students and professionals alike in the field of computing system design, management, and application. This book will also be beneficial to the general audience and technology enthusiasts who want to expand their knowledge on computer structure.

Download or read book Automated Workflow Scheduling in Self Adaptive Clouds written by G. Kousalya and published by Springer. This book was released on 2017-05-25 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: This timely text/reference presents a comprehensive review of the workflow scheduling algorithms and approaches that are rapidly becoming essential for a range of software applications, due to their ability to efficiently leverage diverse and distributed cloud resources. Particular emphasis is placed on how workflow-based automation in software-defined cloud centers and hybrid IT systems can significantly enhance resource utilization and optimize energy efficiency. Topics and features: describes dynamic workflow and task scheduling techniques that work across multiple (on-premise and off-premise) clouds; presents simulation-based case studies, and details of real-time test bed-based implementations; offers analyses and comparisons of a broad selection of static and dynamic workflow algorithms; examines the considerations for the main parameters in projects limited by budget and time constraints; covers workflow management systems, workflow modeling and simulation techniques, and machine learning approaches for predictive workflow analytics. This must-read work provides invaluable practical insights from three subject matter experts in the cloud paradigm, which will empower IT practitioners and industry professionals in their daily assignments. Researchers and students interested in next-generation software-defined cloud environments will also greatly benefit from the material in the book.

Download or read book Adaptive Resource Management and Scheduling for Cloud Computing written by Florin Pop and published by Springer. This book was released on 2016-01-07 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the Second International Workshop on Adaptive Resource Management and Scheduling for Cloud Computing, ARMS-CC 2015, held in Conjunction with ACM Symposium on Principles of Distributed Computing, PODC 2015, in Donostia-San Sebastián, Spain, in July 2015. The 12 revised full papers, including 1 invited paper, were carefully reviewed and selected from 24 submissions. The papers have identified several important aspects of the problem addressed by ARMS-CC: self-* and autonomous cloud systems, cloud quality management and service level agreement (SLA), scalable computing, mobile cloud computing, cloud computing techniques for big data, high performance cloud computing, resource management in big data platforms, scheduling algorithms for big data processing, cloud composition, federation, bridging, and bursting, cloud resource virtualization and composition, load-balancing and co-allocation, fault tolerance, reliability, and availability of cloud systems.

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.

Download or read book Emerging Research in Cloud Distributed Computing Systems written by Bagchi, Susmit and published by IGI Global. This book was released on 2015-03-31 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: Traditional computing concepts are maturing into a new generation of cloud computing systems with wide-spread global applications. However, even as these systems continue to expand, they are accompanied by overall performance degradation and wasted resources. Emerging Research in Cloud Distributed Computing Systems covers the latest innovations in resource management, control and monitoring applications, and security of cloud technology. Compiling and analyzing current trends, technological concepts, and future directions of computing systems, this publication is a timely resource for practicing engineers, technologists, researchers, and advanced students interested in the domain of cloud computing.

Download or read book Job Scheduling Strategies for Parallel Processing written by Dalibor Klusáček and published by Springer. This book was released on 2018-03-21 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 21st International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2017, held in Orlando, FL, USA, in June 2017.The 10 revised full papers presented in this book were carefully reviewed and selected from 20 submissions. The papers cover topics in the fields of design and evaluation of new scheduling approaches; performance evaluation of scheduling approaches; workloads; consideration of additional constraints in scheduling systems; scaling and composition of very large scheduling systems; cloud provider issues; interaction between schedulers on different levels; interaction between applications/workloads; experience reports from production systems or large scale compute campaigns.

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.

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.

Download or read book Hierarchical Scheduling in Parallel and Cluster Systems written by Sivarama Dandamudi and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple processor systems are an important class of parallel systems. Over the years, several architectures have been proposed to build such systems to satisfy the requirements of high performance computing. These architectures span a wide variety of system types. At the low end of the spectrum, we can build a small, shared-memory parallel system with tens of processors. These systems typically use a bus to interconnect the processors and memory. Such systems, for example, are becoming commonplace in high-performance graph ics workstations. These systems are called uniform memory access (UMA) multiprocessors because they provide uniform access of memory to all pro cessors. These systems provide a single address space, which is preferred by programmers. This architecture, however, cannot be extended even to medium systems with hundreds of processors due to bus bandwidth limitations. To scale systems to medium range i. e. , to hundreds of processors, non-bus interconnection networks have been proposed. These systems, for example, use a multistage dynamic interconnection network. Such systems also provide global, shared memory like the UMA systems. However, they introduce local and remote memories, which lead to non-uniform memory access (NUMA) architecture. Distributed-memory architecture is used for systems with thousands of pro cessors. These systems differ from the shared-memory architectures in that there is no globally accessible shared memory. Instead, they use message pass ing to facilitate communication among the processors. As a result, they do not provide single address space.

Download or read book Euro Par 2017 Parallel Processing written by Francisco F. Rivera and published by Springer. This book was released on 2017-08-18 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 23rd International Conference on Parallel and Distributed Computing, Euro-Par 2017, held in Santiago de Compostela, Spain, in August/September 2017. The 50 revised full papers presented together with 2 abstract of invited talks and 1 invited paper were carefully reviewed and selected from 176 submissions. The papers are organized in the following topical sections: support tools and environments; performance and power modeling, prediction and evaluation; scheduling and load balancing; high performance architectures and compilers; parallel and distributed data management and analytics; cluster and cloud computing; distributed systems and algorithms; parallel and distributed programming, interfaces and languages; multicore and manycore parallelism; theory and algorithms for parallel computation and networking; prallel numerical methods and applications; and accelerator computing.

Download or read book Resource Management for Big Data Platforms written by Florin Pop and published by Springer. This book was released on 2016-10-27 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: Serving as a flagship driver towards advance research in the area of Big Data platforms and applications, this book provides a platform for the dissemination of advanced topics of theory, research efforts and analysis, and implementation oriented on methods, techniques and performance evaluation. In 23 chapters, several important formulations of the architecture design, optimization techniques, advanced analytics methods, biological, medical and social media applications are presented. These chapters discuss the research of members from the ICT COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications (cHiPSet). This volume is ideal 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 their potential solutions.

Download or read book Computational Science ICCS 2009 written by Gabrielle Allen and published by Springer. This book was released on 2009-05-21 with total page 940 pages. Available in PDF, EPUB and Kindle. Book excerpt: “There is something fascinating about science. One gets such wholesale returns of conjecture out of such a tri?ing investment of fact. ” Mark Twain, Life on the Mississippi The challenges in succeeding with computational science are numerous and deeply a?ect all disciplines. NSF’s 2006 Blue Ribbon Panel of Simulation-Based 1 Engineering Science (SBES) states ‘researchers and educators [agree]: com- tational and simulation engineering sciences are fundamental to the security and welfare of the United States. . . We must overcome di?culties inherent in multiscale modeling, the development of next-generation algorithms, and the design. . . of dynamic data-driven application systems. . . We must determine better ways to integrate data-intensive computing, visualization, and simulation. - portantly,wemustoverhauloureducationalsystemtofostertheinterdisciplinary study. . . The payo?sformeeting these challengesareprofound. ’The International Conference on Computational Science 2009 (ICCS 2009) explored how com- tational sciences are not only advancing the traditional hard science disciplines, but also stretching beyond, with applications in the arts, humanities, media and all aspects of research. This interdisciplinary conference drew academic and industry leaders from a variety of ?elds, including physics, astronomy, mat- matics,music,digitalmedia,biologyandengineering. Theconferencealsohosted computer and computational scientists who are designing and building the - ber infrastructure necessary for next-generation computing. Discussions focused on innovative ways to collaborate and how computational science is changing the future of research. ICCS 2009: ‘Compute. Discover. Innovate. ’ was hosted by the Center for Computation and Technology at Louisiana State University in Baton Rouge.

Download or read book Ambient Communications and Computer Systems written by Yu-Chen Hu and published by Springer Nature. This book was released on 2022-05-07 with total page 620 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features high-quality, peer-reviewed papers from the Fourth International Conference on Recent Advancements in Computer, Communication, and Computational Sciences (RACCCS 2021), held at Aryabhatta College of Engineering and Research Center, Ajmer, India, on August 20–21, 2021. Presenting the latest developments and technical solutions in computational sciences, it covers a variety of topics, such as intelligent hardware and software design, advanced communications, intelligent computing technologies, advanced software engineering, the web and informatics, and intelligent image processing. As such, it helps those in the computer industry and academia to use the advances in next-generation communication and computational technology to shape real-world applications.

Download or read book Cloud Computing for Data Intensive Applications written by Xiaolin Li and published by Springer. This book was released on 2014-12-02 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a range of cloud computing platforms for data-intensive scientific applications. It covers systems that deliver infrastructure as a service, including: HPC as a service; virtual networks as a service; scalable and reliable storage; algorithms that manage vast cloud resources and applications runtime; and programming models that enable pragmatic programming and implementation toolkits for eScience applications. Many scientific applications in clouds are also introduced, such as bioinformatics, biology, weather forecasting and social networks. Most chapters include case studies. Cloud Computing for Data-Intensive Applications targets advanced-level students and researchers studying computer science and electrical engineering. Professionals working in cloud computing, networks, databases and more will also find this book useful as a reference.