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 issues of software performance is bottlenecks that have not been investigated much 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. The 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 the strength of the bottleneck, the response time and the 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 to a case study, and a comprehensive comparison is presented. (C) 2015 Sharif University of Technology. All rights reserved.