Network-aware meta-scheduling in advance with autonomous self-tuning system
Future Generation Computer Systems
Improving cloud infrastructure utilization through overbooking
Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference
Cloudy with a Chance of Load Spikes: Admission Control with Fuzzy Risk Assessments
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
Hi-index | 0.00 |
One of the main challenges of scheduling algorithms in Grid environment is the autonomy of sites, which makes it difficult for the grid scheduler to estimate the exact cost of a task execution on different sites. In this paper, we present a solution for this problem based on data history (workload traces) and time series techniques. The main focus of this work is devoted to forecasting the task waiting time in a resource queue, which is under the control of a local scheduler with distinctive scheduling policy. The main contribution of this work is the consideration of a special property of the grid resources, the dynamic membership, i.e. a resource may exit and then come back to the grid environment repeatedly. When the resource belongs to the grid environment, its workload trace (log file) is considered as a correct log. On the other hand, when the resource leaves the grid, the log file during this period is considered as a defective part of the trace. As the defective parts contain some useful information, after repairing these defective parts, they can be used for forecasting purposes. Of this, we employ state-space model along with the associated Kalman recursions in conjunction with the Expectation-Maximization algorithm to repair the defective waiting time series such as a correct log file by which the resource seems never to have left the grid. The experimental results on a number of workload logs demonstrated that this approach can achieve an average prediction error, between 22 and 64% less than those incurred by other rival methods. Copyright © 2009 John Wiley & Sons, Ltd.