Automated Workflow Scheduling in Self-Adaptive Clouds Automated Workflow Scheduling in Self-Adaptive Clouds
Computer Communications and Networks

Automated Workflow Scheduling in Self-Adaptive Clouds

Concepts, Algorithms and Methods

G. Kousalya 및 다른 저자
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출판사 설명

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.


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.

장르
컴퓨터 및 인터넷
출시일
2017년
5월 25일
언어
EN
영어
길이
242
페이지
출판사
Springer International Publishing
판매자
Springer Nature B.V.
크기
4.8
MB
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