A Multi-Objective Approach to Model-Driven Performance Bottlenecks Mitigation

Software Performance Engineering (SPE) evaluates the key performance factors such as response time and utilization in the entire life cycle of software development. One of the important issue of software performance is bottlenecks that is not investigated more till now in the process of SPE. Meanwhile, Bottleneck detection and mitigation in software modeling stage is quality-centered and cost effective. Layered bottleneck is a type of bottleneck that occurs in systems with layered services and affects its utilization more than flat bottlenecks. Presented approach in this paper has selected Layered Queening Network (LQN) as an appropriate performance model to present and analyze the layered bottlenecks. The process of SPE from software model to performance model has been automatically implemented. Also, an optimization stage is added to find the best specification of software model in a way that strength of the bottleneck, response time and cost will be minimized. To assess the proposed solution two recently proposed multi-objective gravitational search algorithms are employed. To evaluate the effectiveness of the applied algorithms, two well-known multi-objective algorithms: NSGA-II and MOPSO are also applied for a case study and a comprehensive comparison is presented.