Name
Abstract | ||
|---|---|---|
The popularity of cloud service spurs the increasing demands of virtual resources to the service vendors. Along with the promising business opportunities, it also brings new technique challenges such as effective capacity planning and instant cloud resource provisioning. In this paper, we describe our research efforts on improving the service quality for the capacity planning and instant cloud resource provisioning problem. We first formulate both of the two problems as a generic cost-sensitive prediction problem. Then, considering the highly dynamic environment of cloud, we propose an asymmetric and heterogeneous measure to quantify the prediction error. Finally, we design an ensemble prediction mechanism by combining the prediction power of a set of prediction techniques based on the proposed measure. To evaluate the effectiveness of our proposed solution, we design and implement an integrated prototype system to help improve the service quality of the cloud. Our system considers many practical situations of the cloud system, and is able to dynamically adapt to the changing environment. A series of experiments on the IBM Smart Cloud Enterprise (SCE) trace data demonstrate that our method can significantly improve the service quality by reducing the resource provisioning time while maintaining a low cloud overhead. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/TNSM.2013.051913.120278 | IEEE Transactions on Network and Service Management |
Keywords | Field | DocType |
ibm smart cloud enterprise,service quality,cloud service,integrated prototype system,generic cost-sensitive prediction problem,service vendors,cloud analytics,virtual machines,cloud computing,resource allocation,instant cloud resource provisioning problem,virtualisation,instant provisioning,virtual resources,data mining,cloud service quality,ibm sce,capacity planning,instant vm provisioning,virtual enterprises,business opportunities,virtualization | Virtual machine,Service quality,Computer science,Computer network,Capacity planning,Provisioning,Cloud computing security,Resource allocation,Cloud testing,Distributed computing,Cloud computing | Journal |
Volume | Issue | ISSN |
10 | 3 | 1932-4537 |
Citations | PageRank | References |
41 | 1.08 | 23 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yexi Jiang | 1 | 253 | 14.60 |
| Chang-Shing Perng | 2 | 478 | 35.92 |
| Tao Li | 3 | 7216 | 393.45 |
| Rong N. Chang | 4 | 346 | 29.75 |