Title: A Bayesian approach to performance modelling for multi-tenant applications using Gaussian models

Authors: Junling Zhang; Shijun Liu; Lizhen Cui; Lei Wu; Li Pan

Addresses: School of Computer Science and Technology, Shandong University, No. 1500, Shunhua Road, High Tech Development Zone, Jinan, 250101, China ' School of Computer Science and Technology, Shandong University, No. 1500, Shunhua Road, High Tech Development Zone, Jinan, 250101, China; Key Laboratory of Shandong Province for Software Engineering, Jinan, 250101, China ' School of Computer Science and Technology, Shandong University, No. 1500, Shunhua Road, High Tech Development Zone, Jinan, 250101, China ' School of Computer Science and Technology, Shandong University, No. 1500, Shunhua Road, High Tech Development Zone, Jinan, 250101, China ' School of Computer Science and Technology, Shandong University, No. 1500, Shunhua Road, High Tech Development Zone, Jinan, 250101, China

Abstract: Accurately predicting response times of service queries is necessary for deployments optimisation in the multi-tenant applications system. This task is particularly challenging owing to the fact that the mixes of tenants with different business scale and operating characteristics and the interaction among the concurrently running queries have a great impact on the response time of queries in the multi-tenant applications systems, and an accurate model needs to capture them. In this paper, our goal is to build such a performance model for the interactions of multi-tenant using an experiment-driven modelling approach. We use a Bayesian approach and build novel Gaussian models that take into account a variety of factors that influence the response time of each interaction that is sent from the different tenants in the multi-tenant environments. We experimentally demonstrate that our models are accurate and effective which have an average prediction error of 12.6% in the worst case.

Keywords: service performance management; Bayesian approach; experiment-driven modelling; performance modelling; multi-tenant services; Gaussian models; response times; software as a service; SaaS.

DOI: 10.1504/IJHPCN.2016.074667

International Journal of High Performance Computing and Networking, 2016 Vol.9 No.1/2, pp.150 - 159

Available online: 12 Feb 2016 *

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