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.
['Xianwen Hao', 'Yu Dai', 'Bin Zhang', 'Tingwei Chen', 'Lei Yang']
QoS-driven grid resource selection based on novel neural networks