@article{M910540FA,
title = "Technique to Reduce Container Restart for Improving Execution Time of 
Container Workflow in Kubernetes Environments",
journal = "The Transactions of the Korea Information Processing Society",
year = "2024",
issn = "null",
doi = "https://doi.org/10.3745/TKIPS.2024.13.3.91",
author = "Taeshin Kang, Heonchang Yu",
keywords = "Resource Management, Kubernetes, Container Workflow, Memory Oversubscription",
abstract = "The utilization of container virtualization technology ensures the consistency and portability of data-intensive and memory volatile 
workflows. Kubernetes serves as the de facto standard for orchestrating these container applications. Cloud users often overprovision 
container applications to avoid container restarts caused by resource shortages. However, overprovisioning results in decreased CPU and 
memory resource utilization. To address this issue, oversubscription of container resources is commonly employed, although excessive 
oversubscription of memory resources can lead to a cascade of container restarts due to node memory scarcity. Container restarts can 
reset operations and impose substantial overhead on containers with high memory volatility that include numerous stateful applications. 
This paper proposes a technique to mitigate container restarts in a memory oversubscription environment based on Kubernetes. The 
proposed technique involves identifying containers that are likely to request memory allocation on nodes experiencing high memory usage 
and temporarily pausing these containers. By significantly reducing the CPU usage of containers, an effect similar to a paused state is 
achieved. The suspension of the identified containers is released once it is determined that the corresponding node's memory usage 
has been reduced. The average number of container restarts was reduced by an average of 40% and a maximum of 58% when executing
a high memory volatile workflow in a Kubernetes environment with the proposed method compared to its absence. Furthermore, the 
total execution time of a container workflow is decreased by an average of 7% and a maximum of 13% due to the reduced frequency
of container restarts."
}