QoS-Driven grid resource selection based on novel neural networks

Authors:
Xianwen Hao;Yu Dai;Bin Zhang;Tingwei Chen;Lei Yang
Affiliations:
College of Information Science and Engineering, Northeastern University, Shenyang, China;College of Information Science and Engineering, Northeastern University, Shenyang, China;College of Information Science and Engineering, Northeastern University, Shenyang, China;College of Information Science and Engineering, Northeastern University, Shenyang, China;College of Information Science and Engineering, Northeastern University, Shenyang, China
Venue:
GPC'06 Proceedings of the First international conference on Advances in Grid and Pervasive Computing
Year:
2006

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Abstract

The dynamics nature of grid environment brings challenges for applications to offer nontrivial QoS on distributed, heterogeneous resources. It's a better way to select the suitable grid resources constrained by QoS. In this paper we propose the application QoS model and metrics as the standard of resource selection. We also give consideration of the existence of data dependence between the tasks composing an application and apply it to the QoS model. And we solve the resource selection problem efficiently using novel neural networks.