An adaptive meta-scheduler for data-intensive applications
by Hai Jin, Xuanhua Shi, Weizhong Qiang, Deqing Zou
International Journal of Grid and Utility Computing (IJGUC), Vol. 1, No. 1, 2005

Abstract: In data-intensive applications, such as high-energy physics, bio-informatics, we encounter applications involving numerous jobs that access and generate large datasets. Effective scheduling of such applications is a challenge, due to the need to consider for both computational resources and data storage resources. In this paper, we describe an adaptive scheduling model that considers availability of computational, storage and network resources. Based on this model we implement a scheduler used in our campus grid. The results achieved by our scheduler have been analysed by comparing with greedy algorithm that is widely used in computational grids and some data grids.

Online publication date: Mon, 16-May-2005

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Grid and Utility Computing (IJGUC):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com