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 issues are also outlined. All of those technologies have
formed the foundation for the green computing that we know of
today."
General
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