Evolutionary Based Solutions for Green Computing

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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Khan, Samee Ullah (Επιμελητής έκδοσης), Kołodziej, Joanna (Επιμελητής έκδοσης), Li, Juan (Επιμελητής έκδοσης), Zomaya, Albert Y. (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Σειρά:Studies in Computational Intelligence, 432
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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245 1 0 |a Evolutionary Based Solutions for Green Computing  |h [electronic resource] /  |c edited by Samee Ullah Khan, Joanna Kołodziej, Juan Li, Albert Y. Zomaya. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2013. 
300 |a XX, 256 p.  |b online resource. 
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490 1 |a Studies in Computational Intelligence,  |x 1860-949X ;  |v 432 
520 |a 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.   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. 
650 0 |a Engineering. 
650 0 |a Renewable energy resources. 
650 0 |a Artificial intelligence. 
650 0 |a Computational intelligence. 
650 0 |a Renewable energy sources. 
650 0 |a Alternate energy sources. 
650 0 |a Green energy industries. 
650 1 4 |a Engineering. 
650 2 4 |a Computational Intelligence. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
650 2 4 |a Renewable and Green Energy. 
650 2 4 |a Renewable and Green Energy. 
700 1 |a Khan, Samee Ullah.  |e editor. 
700 1 |a Kołodziej, Joanna.  |e editor. 
700 1 |a Li, Juan.  |e editor. 
700 1 |a Zomaya, Albert Y.  |e editor. 
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776 0 8 |i Printed edition:  |z 9783642306587 
830 0 |a Studies in Computational Intelligence,  |x 1860-949X ;  |v 432 
856 4 0 |u http://dx.doi.org/10.1007/978-3-642-30659-4  |z Full Text via HEAL-Link 
912 |a ZDB-2-ENG 
950 |a Engineering (Springer-11647)