Execution Time Prediction Using Rough Set Theory in Hybrid Cloud

Execution time prediction is an important issue in cloud computing. Predicting the execution time fast and accurately not only can help users to schedule jobs smarter, but also maximize the throughput and minimize the resource consumption of cloud platform. While hybrid cloud provides methods to fed...

Full description

Saved in:
Bibliographic Details
Published in2012 9th International Conference on Ubiquitous Intelligence and Computing and 9th International Conference on Autonomic and Trusted Computing pp. 729 - 734
Main Authors Chih-Tien Fan, Yue-Shan Chang, Wei-Jen Wang, Shyan-Ming Yuan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2012
Subjects
Approximation methods
Cloud computing
Dynamic scheduling
Educational institutions
Error analysis
Execution Time Prediction
History Based Approach
Hybrid Cloud
Private Cloud
Processor scheduling
Public Cloud
Rough Set Theory
Rough Sets
Set theory
Online AccessGet full text

Cover

More Information
Summary:Execution time prediction is an important issue in cloud computing. Predicting the execution time fast and accurately not only can help users to schedule jobs smarter, but also maximize the throughput and minimize the resource consumption of cloud platform. While hybrid cloud provides methods to federate multiple cloud platforms, different cloud platforms have different resource attributes, which will increase the difficulties to predict a job's execution time. In this paper, we exploit Rough Set Theory (RST), which is a well-known prediction technique that uses the historical data, to predict the execution time of jobs. The evaluation presents that RST can utilize the accuracy of the execution time, while the decision can be made in a short period of time.
ISBN:1467330841
9781467330848
DOI:10.1109/UIC-ATC.2012.41