Tian W., Zhao Y. Optimized Cloud Resource Management and Scheduling: Theory and Practice

Morgan Kaufmann, 2015. — 284 p. — ISBN: 978-0-12-801476-9.Optimized Cloud Resource Management and Scheduling identifies research directions and technologies that will facilitate efficient management and scheduling of computing resources in cloud data centers supporting scientific, industrial, business, and consumer applications. It serves as a valuable reference for systems architects, practitioners, developers, researchers and graduate level students.
Explains how to optimally model and schedule computing resources in cloud computing.
Provides in depth quality analysis of different load-balance and energy-efficient scheduling algorithms for cloud data centers and Hadoop clusters.
Introduces real-world applications, including business, scientific and related case studies.
Discusses different cloud platforms with real test-bed and simulation tools.An Introduction to Cloud Computing
Big Data Technologies and Cloud Computing
Resource Modeling and Definitions for Cloud Data Centers
Cloud Resource Scheduling Strategies
Load Balance Scheduling for Cloud Data Centers
Energy-efficient Allocation of Real-time Virtual Machines in Cloud Data Centers Using Interval-packing Techniques
Energy Efficiency by Minimizing Total Busy Time of Offline Parallel Scheduling in Cloud Computing
Comparative Study of Energy-efficient Scheduling in Cloud Data Centers
Energy Efficiency Scheduling in Hadoop
Maximizing Total Weights in Virtual Machines Allocation
A Toolkit for Modeling and Simulation of Real-time Virtual Machine Allocation in a Cloud Data Center
Toward Running Scientific Workflows in the Cloud