Temporal QOS Management in Scientific Cloud Workflow Systems
“Temporal QOS Management in Scientific Cloud Workflow Systems” by Liu, Xiao, published by Elsevier S & T in 2012, is a focused exploration of cloud computing’s role in scientific applications. This edition, comprising 154 pages, delves into how cloud workflows facilitate large-scale data and computation-intensive tasks, such as earthquake modeling and weather forecasting. The book addresses the complexities of application modeling and execution within cloud infrastructures, emphasizing the importance of temporal constraints like milestones and deadlines.
Readers will find a comprehensive framework designed to support the lifecycle of time-constrained workflow applications, ensuring timely completion of tasks. The text discusses strategies for monitoring and controlling activity duration as a measure of system performance. By presenting innovative concepts and algorithms, this book aims to enhance the performance and usability of scientific cloud workflow systems, making it a valuable resource for professionals in computer science and system administration.
Official synopsis Publisher
Cloud computing can provide virtually unlimited scalable high performance computing resources. Cloud workflows often underlie many large scale data/computation intensive e-science applications such as earthquake modelling, weather forecasting and astrophysics. During application modelling, these sophisticated processes are redesigned as cloud workflows, and at runtime, the models are executed by employing the supercomputing and data sharing ability of the underlying cloud computing infrastructures.
Temporal QOS Management in Scientific Cloud Workflow Systems focuses on real world scientific applications which often must be completed by satisfying a set of temporal constraints such as milestones and deadlines. Meanwhile, activity duration, as a measurement of system performance, often needs to be monitored and controlled. This book demonstrates how to guarantee on-time completion of most, if not all, workflow applications. Offering a comprehensive framework to support the lifecycle of time-constrained workflow applications, this book will enhance the overall performance and usability of scientific cloud workflow systems.
- Explains how to reduce the cost to detect and handle temporal violations while delivering high quality of service (QoS)
- Offers new concepts, innovative strategies and algorithms to support large-scale sophisticated applications in the cloud
- Improves the overall performance and usability of cloud workflow systems
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