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The grid style of computing treats collections of similar IT resources holistically as a single pool, while exploiting the distinct nature of individual resources within the pool.

To address simultaneously the problems of monolithic systems and fragmented resources, grid computing achieves a balance between the benefits of holistic resource management and flexible independent resource control.

Finally, the candidate variables are ordered in the light of the average importance measure and some significant variables are then selected by a thresholding rule.

There is no need for peak workloads, because capacity can be easily added or reallocated from the resource pools as needed. Because the physical and logical structures are separate, the physical storage of data can be managed without affecting the access to logical storage structures.

For example, one policy might be to dedicate enough processing power to a web server that it can always provide sub-second response time.

That rule could be fulfilled in different ways by the provisioning software in order to balance the requests of all consumers.

In particular, PBoost GA has stronger ability to exclude redundant variables.

The authors are very grateful to the anonymous referees and the editor for their critical comments which helped improve the presentation greatly.

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