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

TL;DR

This paper introduces a fully distributed algorithm, DRA, that optimally minimizes resource consumption in cloud applications by dynamically migrating components based solely on local information, addressing scalability issues.

Contribution

The paper presents DRA, a novel fully distributed algorithm that guarantees optimal resource minimization in cloud applications without centralized control.

Findings

DRA converges to the optimal solution.

DRA effectively reduces resource consumption.

The algorithm is scalable and dynamic.

Abstract

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. Specifically, DRA migrates the inter-communicating components of an application, such as processes or virtual machines, close to each other to minimize the total resource consumption. The migration decisions are made in a dynamic way and based only on local information. We prove that DRA achieves convergence and results always in the optimal solution.