Managing Dynamic Enterprise and Urgent Workloads on Clouds using Layered Queuing and Historical Performance Models
Bacigalupo, D.A., van Hemert, J., Chen, X., Usmani, A., Chester, A.P., He, L., Dillenberger, D.N., Wills, G. B., Gilbert, L. and Jarvis, S.A. (2011) Managing Dynamic Enterprise and Urgent Workloads on Clouds using Layered Queuing and Historical Performance Models. Simulation Modelling Practice and Theory, 19 (6). pp. 1479-1495.
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The automatic allocation of enterprise workload to resources can be enhanced by being able to make what–if response time predictions whilst different allocations are being considered. We experimentally investigate an historical and a layered queuing performance model and show how they can provide a good level of support for a dynamic-urgent cloud environment. Using this we define, implement and experimentally investigate the effectiveness of a prediction-based cloud workload and resource management algorithm. Based on these experimental analyses we: (i) comparatively evaluate the layered queuing and historical techniques; (ii) evaluate the effectiveness of the management algorithm in different operating scenarios; and (iii) provide guidance on using prediction-based workload and resource management.
|Uncontrolled Keywords:||pcav hpsg cloud peer business distributed business|
|Subjects:||Q Science > QA Mathematics > QA76 Computer software|
|Divisions:||Faculty of Science > Computer Science|
|Depositing User:||Matt Leeke|
|Date Deposited:||31 Mar 2011 09:09|
|Last Modified:||23 Feb 2012 09:08|
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