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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Evolutionary Based Solutions for Green Computing

Evolutionary Based Solutions for Green Computing

Khan, Samee Ullah
Kolodziej, Joanna
Li, Juan

Paperback

Series: Studies in Computational Intelligence, Book 432

Technology & EngineeringGeneral ComputersGeneral Science

ISBN10: 364243066X
ISBN13: 9783642430664
Publisher: Springer Nature
Published: Sep 20 2014
Pages: 256
Weight: 0.86
Height: 0.58 Width: 6.14 Depth: 9.21
Language: English

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.

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