By Daron G. Green (auth.), Jukka Riekki, Mika Ylianttila, Minyi Guo (eds.)

ISBN-10: 3642207537

ISBN-13: 9783642207532

This e-book constitutes the court cases of the sixth foreign convention, GPC 2011, held in Oulu, Finland in may well 2011.

The 28 revised complete papers have been rigorously revised and chosen from sixty two submissions and concentrate on the themes cloud, cluster, and grid computing; peer-to-peer computing; purposes and HCI; modeling and verification; carrier architectures; middleware; and sensor networks.

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Additional info for Advances in Grid and Pervasive Computing: 6th International Conference, GPC 2011, Oulu, Finland, May 11-13, 2011. Proceedings

Example text

In first part, a self-organization algorithm, partialView and groupView are generated based on system parameters such as the size of partialView(k), the number of group (groupCount) and group member (groupSize). Figure 2 shows the pseudo-code of the self-organization algorithm, which is executed once before the message dissemination algorithm is performed. At the beginning, the self-organization algorithm fetches the values of groupCount, groupSize and partial ViewSize (lines 2-4 in Fig. 2) and these values are determined by system configuration.

The price fluctuates periodically depending on the relationship between supply and demand of the Spot Instance capacity. A Leasing Instances Based Billing Model for Cloud Computing 35 From the example we can conclude that although Amazon EC2's model can avoid complex cloud accounting operations, it cannot guarantee fairness among the end users. Whereas billing according to resource usage could be more fair, however, nowadays there aren’t appropriate business models and trust mechanisms, so it is difficult to apply in the real world.

Therefore, it is essential to develop new efficient methods to reconcile power and performance management in data centers. In contrast to existing related works, we propose a smart consolidation approach for energy efficiency by taking into account both performance and energy costs. For this purpose, we present an optimization model that includes two objective functions, one for power cost and another for the performance. In addition, we cope with the cost of VM migration and turning servers on or off in our consolidation model.

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Advances in Grid and Pervasive Computing: 6th International Conference, GPC 2011, Oulu, Finland, May 11-13, 2011. Proceedings by Daron G. Green (auth.), Jukka Riekki, Mika Ylianttila, Minyi Guo (eds.)


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