An Optimal Fully Distributed Algorithm to Minimize the Resource Consumption of Cloud Applications

According to the pay-per-use model adopted in clouds, the more the resources consumed by an application running in a cloud computing environment, the greater the amount of money the owner of the corresponding application will be charged. Therefore, applying intelligent solutions to minimize the resource consumption is of great importance. Because centralized solutions are deemed unsuitable for large-distributed systems or large-scale applications, we propose a fully distributed algorithm (called DRA) to overcome the scalability issues. The aforementioned problem can be solved by identifying an assignment scheme between the interacting components of an application, such as processes and virtual machines, and the computing nodes of a cloud system, such that the total amount of resources consumed by the respective application is minimized. The decisions for the transition from one assignment scheme to another one are made in a dynamic way and based only on local information. It should be stressed that DRA achieves convergence and always results in the optimal solution. We also show, through an experimental evaluation, that DRA achieves up to 55% network cost reduction when compared to the most recent algorithm in the literature.