CSMD: Container state management for deployment in cloud data centers

IF 6.2 2区计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS Future Generation Computer Systems-The International Journal of Escience Pub Date : 2024-08-28 DOI:10.1016/j.future.2024.107495

Shubha Brata Nath , Sourav Kanti Addya , Sandip Chakraborty , Soumya K. Ghosh

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Abstract

As the containers are lightweight in resource usage, they are preferred for cloud and edge computing service deployment. Containers serve the requests whenever a user sends a query; however, they remain idle when no user request comes. Again, improving the consolidation ratio of container deployments is essential to ensure fewer servers are used in a cloud data center with an optimal resource balance. To increase the consolidation ratio of a cloud data center, in this paper, we propose a system called Container State Management for Deployment (CSMD) to manage the container states. CSMD uses an algorithm to checkpoint the idle containers so that their resources can be released. The new containers are deployed using the released resources in a server. In addition, CSMD uses an algorithm to check the container status periodically, and the containers are resumed from the checkpoint state when the user requests them. We evaluate CSMD in Amazon Elastic Compute Cloud (Amazon EC2) by performing efficient state management of the containers. The experiments in the Amazon cloud show that the proposed CSMD system is superior to the existing algorithms as the proposed system increases the consolidation ratio of data centers.

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CSMD：用于云数据中心部署的容器状态管理

由于容器在资源使用方面是轻量级的，因此是云计算和边缘计算服务部署的首选。只要用户发送查询，容器就会为请求提供服务；但当没有用户请求时，容器就会处于闲置状态。同样，提高容器部署的整合率对于确保在云数据中心使用更少的服务器并实现最佳资源平衡至关重要。为了提高云数据中心的整合率，我们在本文中提出了一种名为 "部署容器状态管理"（CSMD）的系统来管理容器状态。CSMD 使用一种算法对闲置容器进行检查点，以便释放其资源。新容器将使用服务器中释放的资源进行部署。此外，CSMD 还使用一种算法定期检查容器状态，并在用户请求时从检查点状态恢复容器。我们在亚马逊弹性计算云（Amazon EC2）中对 CSMD 进行了评估，对容器进行了有效的状态管理。在亚马逊云中的实验表明，拟议的 CSMD 系统优于现有算法，因为拟议的系统提高了数据中心的整合率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Future Generation Computer Systems-The International Journal of Escience 工程技术-计算机：理论方法

CiteScore

19.90

自引率

2.70%

发文量

376

审稿时长

10.6 months

期刊介绍： Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.

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