Learning Cooperation in Collaborative Grid Environments to Improve Cover Load Balancing Delivery

Author

Paletta, Mauricio ; Herrero, Pilar

Author_Institution

Dipt. de Cienc. y Tecnol., UNEG

Volume

2

fYear

2008

fDate

9-12 Dec. 2008

Firstpage

399

Lastpage

402

Abstract

This paper complements the research carried out on the CAM (Collaborative/Cooperative Awareness Management) model with the inclusion of a new learning strategy based on the historical information of previous collaboration/cooperation with the aim to predict future behavior as well as for optimizing purposes. This strategy is based on neural network technology, specifically on Radial Based Function Network (RBFN). Results show that a RBFN properly configured to represent this problem can successfully learn from the data associated to the cooperation in the Grid because it reaches an acceptable average error.

Keywords

grid computing; groupware; learning (artificial intelligence); radial basis function networks; resource allocation; CAM; collaborative grid environments; cooperative awareness management model; learning strategy; load balancing delivery; neural network technology; radial based function network; CADCAM; Computer aided manufacturing; Conference management; Environmental management; Intelligent agent; International collaboration; Load management; Neural networks; Predictive models; Technology management; CAM; Grid Computing; Learning; RBFN;

fLanguage

English

Publisher

ieee

Conference_Titel

Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on

Conference_Location

Sydney, NSW

Print_ISBN

978-0-7695-3496-1

Type

conf

DOI

10.1109/WIIAT.2008.38

Filename

4740656