Scheduled System Maintenance:
On Monday, April 27th, IEEE Xplore will undergo scheduled maintenance from 1:00 PM - 3:00 PM ET (17:00 - 19:00 UTC). No interruption in service is anticipated.
By Topic

Design of an artificial-neural-network-based application-oriented grid resource discovery service

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Hao-peng Chen ; Sch. of Software, Shanghai Jiao Tong Univ., China ; Jian-wei Jiang ; Bao-wen Zhang

This paper puts forward a design of artificial-neural-network-based (ANN-based) application-oriented grid resource discovery service to enable users to dynamically discover the grid resources which are suitable for their applications. The core of this service is an ANN-based grid resource classifier, which periodically accesses the metacomputing directory service and dynamically classifies the grid resources into application-oriented categories according to the real-time state of grid computing environment Users can invoke this service and pass the application type as a parameter to discover the current most suitable grid resources. Grid resource allocation manager also can interact with this service to improve its practicability and efficiency.

Published in:

Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on  (Volume:4 )

Date of Conference:

26-29 Aug. 2004