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, Adam P., He, Ligang, Dillenberger, D.N., Wills, G. B., Gilbert, L. and Jarvis, Stephen 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. ISSN 1569-190XFull text not available from this repository.
Official URL: http://dx.doi.org/10.1016/j.simpat.2011.01.007
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.
|Item Type:||Journal Article|
|Subjects:||Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software|
|Divisions:||Faculty of Science > Computer Science|
|Journal or Publication Title:||Simulation Modelling Practice and Theory|
|Date:||1 February 2011|
|Page Range:||pp. 1479-1495|
|Access rights to Published version:||Restricted or Subscription Access|
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