Performance prediction for Grid workflow activities based on features-ranked RBF network

• 作 者: Wang Jie Duan Rubing Farrukh N
• 机 构: Institute of Computing Technology,Institute of Computer Science,Graduate University of Chinese Acade
• 出 处: 高技术通讯（英文版）
• 发表日期: 2004年期
• 关键词: performance prediction radial basis function (RBF) neural network features rank
• 基金项目: the European Union through the IST-034601 edutaingrid project

Accurate performance prediction of Grid workflow activities can help Grid schedulers map activities to appropriate Grid sites. This paper describes an approach based on features-ranked RBF neural network to predict the performance of Grid workflow activities. Experimental results for two kinds of real world Grid workflow activities are presented to show effectiveness of our approach.