Horizontal and Vertical Self-Adaptive Cloud Controller with Reward Optimization for Resource Allocation
Jesus Alejandro Cardenes Cabre, Doina Precup, Ricardo Sanz · 2017
Over-booking or under-booking of computing resources leads to higher cost and performance degradation of web applications. To optimize the performance of web applications, access to the resources has to be dynamically controlled ensuring maximum cost-performance ratio of the application while fulfilling requirements. To simplify the design of dynamic cloud controllers, we propose a horizontal and vertical scalability self-aware agent defined by a self-adaptive fuzzy logic with an oriented random optimizer based on reward and memory. The algorithm dynamically adjusts the membership functions and their relationship, maximizing the reward of the system while considering the cost related to the deployment of new resources. The evaluation of the controller under real cloud workload reveals the ability of the algorithm to maximize the performance of the web application based on the target parameters given by an operator.