doi: 10.4304/jsw.9.4.921-925
An Greedy-Based Job Scheduling Algorithm in Cloud Computing
- 1 College of Computer Science, Chongqing University, Chongqing 400044, China
- 2 Key Laboratory of Dependable Service Computing in Cyber Physical Society ,Ministry of Education,Chongqing University, Chongqing 400044, China
- 3 College of Computer Science and Information Engineering, Guangxi Normal University, Guilin 541004, China
Abstract
Nowadays/cloud computing has become a popular platform for scientific applications. Cloud computing intends to share a large number of resources such as equipments for storage and computation, and information and knowledge for scientific researches. Job scheduling algorithm is one of the most challenging theoretical issues in the cloud computing area. How to use cloud computing resources efficiently and increase user satisfaction with jobs scheduling system is one of the cloud computing service providers important goals. Some intensive researches have been done in the area of job scheduling of cloud computing. In this paper we have proposed Greedy-Based Algorithm in cloud computing. In order to prove our opinions we will process this artical as the following steps. First of all, we will classify tasks based on QoS. Then, according to the tasks categories, we will select the appropriate branch of the function and compute the justice evaluation. This will also reflects the greedy algorithm to select local optimum. Compare to other methods, it can decrease the completion time of submitted jobs and increases the user satisfaction.
Keywords
- cloud computing
- job scheduling
- Greedy-
How to Cite
Ji Li, Longhua Feng, and Shenglong Fang, "An Greedy-Based Job Scheduling Algorithm in Cloud Computing," Journal of Software, vol. 9, no. 4, pp. 921-925, 2014. https://doi.org/ 10.4304/jsw.9.4.921-925
Copyright & License
Copyright © 2014 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
