Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

A Resource-aware Container Management Scheme in a Heterogeneous Cluster

Version 1 : Received: 11 May 2021 / Approved: 11 May 2021 / Online: 11 May 2021 (10:31:35 CEST)

How to cite: Chen, Y. A Resource-aware Container Management Scheme in a Heterogeneous Cluster. Preprints 2021, 2021050230 (doi: 10.20944/preprints202105.0230.v1). Chen, Y. A Resource-aware Container Management Scheme in a Heterogeneous Cluster. Preprints 2021, 2021050230 (doi: 10.20944/preprints202105.0230.v1).

Abstract

Cloud computing nowadays is not an emerging topic, and virtualization is an indispensable technology to expedite cloud computing to become the next sign of the coming Internet revolution. In real life, scientists never stop at exploring the possibilities from such technology by investigating millions of experiments and applications to enhance the quality of virtual services. However, isolated construction for the virtual machine doesn’t save the technology from unwanted data volumes or insensitive processing time. Containers are created to address such problems, by distributing applications without initiating the entire virtual machine. Docker, as an important player in this game, is an open-source application of the container family. The management tool from Docker containers, Swamskit, does not take heterogeneities in either virtualized containers or physical nodes. There are different nodes in the cluster, and each node is different in configurations, resource availability, or concerning resource, etc. Furthermore, the requirements initiated by different services change all the time. The demand might be CPU-intensive (e.g. Clustering services) and also memory-intensive (e.g. Web services), or completely at the opposite. In this paper, we focus on exploring the Docker container cluster and designing, DRAPS, a resource-aware placement scheme, to improve the system performance in a heterogeneous cluster.

Subject Areas

Container; Docker; Kubernetes; Cloud; Resource Management;

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