Particle Swarm Optimization Algorithm for Container Deployment

Abstract

In recent years, with the development of cloud computing, virtualization technology has received widespread attention. As a new representative of virtualization technology, containers have been widely used in software development, operation and maintenance, testing and other aspects, such as microservices and Docker Cloud. In cloud data centers, containers have gradually replaced virtual machines (VMs) as a new carrier for cloud tasks. However, with the increasing number of cloud products, the scale of tasks requested by users in cloud data centers continues to expand. The economic cost of tasks in the process of containerized deployment has become a concern of various cloud service vendors. The container deployment cost usually includes the data exchange cost, the image pull cost and the server energy cost. In order to solve the containerized deployment of application tasks in the container cloud environment with the lowest possible container deployment cost, this paper proposes a new cost calculation model in a container cloud environment, and then presents an improved particles swarm algorithm, namely a particle swarm optimization (PSO) algorithm for container deployment (CD-PSO) to provide the best solution for application task loading. Experimental results show that the proposed algorithm has a lower deployment cost than other scheduling algorithms.