arrow
Return

CBuild: Cluster-Oriented Collaborative Image Building for Containers

delete2025-09-01
delete0
delete
OA
AI
Z
Zhuo Huang
H
Hao Fan
T
Tang Bin
S
Song Wu
余辰 (Yu Chen)
H
Hai Jin
DOI:10.1109/TC.2025.3575912delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Starting a container needs to build a container image layer-by-layer if the required image is not available. However, the image building involves downloading a large amount of data, which significantly delays the development and deployment of containerized services. To reduce data downloads and accelerate image building, current methods typically focus on improving data sharing through reconstructing images. Unfortunately, these approaches show limited performance improvement in clusters as they only improve data sharing on a single node. In this paper, we find that there are significant duplicated remote file downloads between nodes in a cluster. Accordingly, we propose cBuild, a distributed file cache to minimize costly image data downloads in cluster environments. Specifically, to enable inter-node image data sharing, cBuild designs a non-intrusive interception mechanism based on network namespace, instead of directly detecting building instructions that dirty images. Based on the distribution characteristics of duplicated files in layers, cBuild places image files among nodes in a balanced manner to prevent transfer bottlenecks caused by hotspot nodes and employs a layer-aware searching strategy to quickly locate the desired files. We implement cBuild on the basis of Docker. Experiments show that cBuild improves building speed by up to 15.3<inline-formula><tex-math notation="LaTeX">$\times$</tex-math></inline-formula> and reduces the data downloading by 80%.
Keywords:
Container
image building
Dockerfile
distributed

Journal

IEEE Transactions on Computers cover
IEEE Transactions on Computers
IF:
3.8
Papers:
5.3K
Citations:
9.8K

Organization

H
huazhong university of science and technology
Scholars:
2.5W
Papers: 7.6K
Citations: 5