Automated Workflow Scheduling in Self-Adaptive Clouds
Concepts, Algorithms and Methods
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Beschreibung
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) cloudsPresents simulation-based case studies, and details of real-time test bed-based implementationsOffers analyses and comparisons of a broad selection of static and dynamic workflow algorithmsExamines the considerations for the main parameters in projects limited by budget and time constraintsCovers 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.
Dr. G. Kousalya is a Professor in the Department of Computer Science and Engineering at Coimbatore Institute of Technology, Coimbatore, India. Dr. P. Balakrishnan is an Associate Professor in the Department of Computer Science and Engineering at SASTRA University, Thanjavur, India. Dr. C. Pethuru Raj is the chief architect for Reliance Jio Cloud, Bangalore, India. His other publications include the Springer title High-Performance Big-Data Analytics.
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.
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
Autor*in
G. Kousalya
Themen in »Automated Workflow Scheduling in Self-Adaptive Clouds«
Workflow scheduling Cloud computing Workflow modelling and simulation Cloud management optimisation Automated workflow