@article{Bacigalupo2011, abstract = {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.}, author = {DA Bacigalupo and van Hemert, J and ... and GB Wills and L Gilbert and SA Jarvis}, bibsource = {DBLP, http://dblp.uni-trier.de}, date-added = {2011-09-17 20:22:58 +0100}, date-modified = {2014-07-22 17:49:12 +0000}, ee = {http://dx.doi.org/10.1016/j.simpat.2011.01.007}, journal = {Simulation Modelling Practice and Theory}, keywords = {e-Science}, number = {6}, pages = {1479--95}, title = {Managing dynamic enterprise and urgent workloads on clouds using layered queuing and historical performance models}, volume = {19}, year = {2011}}