Full Description
Today's highly parameterized large-scale distributed computing systems may be composed of a large number of various components (computers, databases, etc) and must provide a wide range of services. The users of such systems, located at different (geographical or managerial) network cluster may have a limited access to the system's services and resources, and different, often conflicting, expectations and requirements. Moreover, the information and data processed in such dynamic environments may be incomplete, imprecise, fragmentary, and overloading. All of the above mentioned issues require some intelligent scalable methodologies for the management of the whole complex structure, which unfortunately may increase the energy consumption of such systems. An optimal energy utilization has reached to a point that many information technology (IT) managers and corporate executives are all up in arms to identify scalable solution that can reduce electricity consumption (so that the total cost of operation is minimized) of their respective large-scale computing systems and simultaneously improve upon or maintain the current throughput of the system.
This book in its eight chapters, addresses the fundamental issues related to the energy usage and the optimal low-cost system design in high performance ``green computing'' systems. The recent evolutionary and general metaheuristic-based solutions for energy optimization in data processing, scheduling, resource allocation, and communication in modern computational grids, could and network computing are presented along with several important conventional technologies to cover the hot topics from the fundamental theory of the ''green computing'' concept and to describe the basic architectures of systems. This book points out the potential application areas and provides detailed examples of application case studies in low-energy computational systems. The development trends and open research issuesare also outlined. All of those technologies have formed the foundation for the green computing that we know of today.
Contents
Evolutionary Green Computing Solutions for Distributed Cyber Physical Systems.-Energy-Aware provisioning of HPC services with virtualised web services.-Macro Level Models of Power Consumption for Servers in Distributed System.-Energy and Security Awareness in Evolutionary-driven Grid Scheduling.-Power Consumption Constrained Task Scheduling Using Enhanced Genetic Algorithms.-Thermal Management in Many-Core Systems .-Sustainable and Reliable On-chip Wireless Communication Infrastructure for Massive Muliti-core Systems.-Exploiting Multi-Objective Evolutionary Algorithms for Designing Energy-efficient Solutions to Data Compression and Node .Localization in Wireless Sensor Networks.
