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."

One of the most challenging issues in today s large-scale computational modeling and design is to effectively manage the complex distributed environments, such as computational clouds, grids, ad hoc, and P2P networks operating under various types of users with evolving relationships fraught with uncertainties. In this context, the IT resources and services usually belong to different owners (institutions, enterprises, or individuals) and are managed by different administrators. Moreover, uncertainties are presented to the system at hand in various forms of information that are incomplete, imprecise, fragmentary, or overloading, which hinders in the full and precise resolve of the evaluation criteria, subsequencing and selection, and the assignment scores. Intelligent scalable systems enable the flexible routing and charging, advanced user interactions and the aggregation and sharing of geographically-distributed resources in modern large-scale systems.

This book presents new ideas, theories, models, technologies, system architectures and implementation of applications in intelligent scalable computing systems. In 15 chapters, several important Artificial Intelligence-based techniques, such as fuzzy logic, neural networks, evolutionary, and memetic algorithms are studied and implemented. All of those technologies have formed the foundation for the intelligent scalable computing that we know of today. We believe that this book will serve as a reference for students, researchers, and industry practitioners working or interested in joining interdisciplinary research in the areas of intelligent decision systems using emergent distributed computing paradigms. It will also allow newcomers (students and researchers alike) to grasp key issues and potential solutions on the selected topics.

This book presents new ideas, theories, models, technologies, system architectures and implementation of applications in intelligent scalable computing systems. In 15 chapters, several important Artificial Intelligence-based techniques, such as fuzzy logic, neural networks, evolutionary, and memetic algorithms are studied and implemented. All of those technologies have formed the foundation for the intelligent scalable computing that we know of today. We believe that this book will serve as a reference for students, researchers, and industry practitioners working or interested in joining interdisciplinary research in the areas of intelligent decision systems using emergent distributed computing paradigms. It will also allow newcomers (students and researchers alike) to grasp key issues and potential solutions on the selected topics.

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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.

One of the most challenging issues in today's large-scale computational modeling and design is to effectively manage the complex distributed environments, such as computational clouds, grids, ad hoc, and P2P networks operating under various types of users with evolving relationships fraught with uncertainties. In this context, the IT resources and services usually belong to different owners (institutions, enterprises, or individuals) and are managed by different administrators. Moreover, uncertainties are presented to the system at hand in various forms of information that are incomplete, imprecise, fragmentary, or overloading, which hinders in the full and precise resolve of the evaluation criteria, subsequencing and selection, and the assignment scores. Intelligent scalable systems enable the flexible routing and charging, advanced user interactions and the aggregation and sharing of geographically-distributed resources in modern large-scale systems. This book presents new ideas, theories, models, technologies, system architectures and implementation of applications in intelligent scalable computing systems. In 15 chapters, several important Artificial Intelligence-based techniques, such as fuzzy logic, neural networks, evolutionary, and memetic algorithms are studied and implemented. All of those technologies have formed the foundation for the intelligent scalable computing that we know of today. We believe that this book will serve as a reference for students, researchers, and industry practitioners working or interested in joining interdisciplinary research in the areas of intelligent decision systems using emergent distributed computing paradigms. It will also allow newcomers (students and researchers alike) to grasp key issues and potential solutions on the selected topics. This book presents new ideas, theories, models, technologies, system architectures and implementation of applications in intelligent scalable computing systems. In 15 chapters, several important Artificial Intelligence-based techniques, such as fuzzy logic, neural networks, evolutionary, and memetic algorithms are studied and implemented. All of those technologies have formed the foundation for the intelligent scalable computing that we know of today. We believe that this book will serve as a reference for students, researchers, and industry practitioners working or interested in joining interdisciplinary research in the areas of intelligent decision systems using emergent distributed computing paradigms. It will also allow newcomers (students and researchers alike) to grasp key issues and potential solutions on the selected topics.