Performance Optimization of Cloud Application at Software Architecture Level

Abstract

Due to the limited search space in the existing performance optimization approaches at software architectures of cloud applications (SAoCA) level, it is difficult for these methods to obtain the cloud resource usage scheme with optimal cost-performance ratio. Aiming at this problem, this paper firstly defines a performance optimization model called CAPOM that can enlarge the search space effectively. Secondly, an efficient differential evolutionary optimization algorithm named MODE4CA is proposed to solve the CAPOM model by defining evolutionary operators with strategy pool and repair mechanism. Further, a method for optimizing performance at SAoCA level, called POM4CA is derived. Finally, two problem instances with different sizes are taken to conduct the experiments for comparing POM4CA with the current representative method under the light and heavy workload. The experimental results show that POM4CA method can obtain better response time and spend less cost of cloud resources.