标题：SRConfig: An Empirical Method of Interdependent Soft Configurations for Improving Performance in n-Tier Application
作者：Shi, Yuliang; Zhao, Xudong; Guo, Shanqing; Liu, Shijun; Cui, Lizhen
作者机构：[Shi, Yuliang; Zhao, Xudong; Guo, Shanqing; Liu, Shijun; Cui, Lizhen] Shandong Univ, Sch Comp Sci & Technol, Jinan 250101, Peoples R China.
会议名称：13th IEEE International Conference on Services Computing (SCC)
会议日期：JUN 27-JUL 02, 2016
来源：PROCEEDINGS 2016 IEEE INTERNATIONAL CONFERENCE ON SERVICES COMPUTING (SCC 2016)
关键词：performance; interdependent; soft resources; n-tier; neural network;; tune
摘要：Efficient resources utilization and better system performance are always two important objectives that service providers pursue to enjoy a maximum profit. In this paper, through analyzing experimental measurements, we study the performance impact of interdependent soft resources on an n-tier application benchmark - the RUBiS system. Soft resources are vital factors that influence hardware resources usage and overall application performance. Improper soft configurations can result in correlated bottlenecks and make performance degradation, so tuning the configuration of soft resources is imperative. Based on the experimental measurements, SRConfig method is applied to predict the soft configurations through adopting the back propagation neural network in n-tier application. Experimental results validate the accuracy and efficacy of our method.