用于边缘计算的微型虚拟机和容器的性能分析:重点关注文件和网络I/O

IF 6.2 2区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Kyungwoon Lee , Yunha Choi , Byungchul Tak
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引用次数: 0

摘要

容器虚拟化已经成为边缘计算和雾计算不可或缺的基础。容器提供了几个优点,例如支持扩展、复制任务的能力和减少依赖性。这些优势在边缘和雾环境中尤为重要。然而,一段时间以来,容器虚拟化的安全性一直相对较低。作为回应,microVM技术的出现提供了更强的隔离性和安全性,其性能可与容器相媲美。在这项工作中,与容器相比,我们更好地理解了microVM在边缘和雾计算方面的可行性。我们在不同的工作负载上进行了大量的实验,以测试微虚拟机与容器在几个方面的比较。通过严格的测量和分析,我们得出了几个重要的发现。尽管具有比容器更复杂的体系结构,但在I/O性能方面,微虚拟机的性能与容器相当。在某些I/O工作负载类型中,microvm的性能甚至比容器高出58%。微虚拟机的网络I/O性能可以比容器高2倍。我们提供了关于边缘设备上的微虚拟机性能特征的发现和见解。由于具有更高程度的隔离能力,微虚拟机可以成为边缘计算环境的一种有吸引力的虚拟化技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance analysis of microVMs and containers for edge computing: A focus on file and network I/O
Container virtualization has become an indispensable foundation for edge and fog computing. Containers offer several advantages, such as the support for scaling, the ability to replicate tasks, and reduced dependency. These advantages are especially crucial in the edge and fog environment. However, concerns over a relatively low level of security have followed container virtualization for some time. In response, microVM technology has emerged offering stronger isolation and security with performances comparable to containers. In this work, we provide a better understanding of microVM’s feasibility for edge and fog computing compared to containers. We conduct extensive experiments on diverse workloads to test how microVMs compare against containers in several aspects. Through rigorous measurements and analysis, we extract several important findings. Despite having a more complex architecture than containers, microVMs perform comparably to the containers in terms of I/O performance. MicroVMs can even outperform containers in certain I/O workload types by 58 %. Network I/O performance of microVMs can be 2× better than containers. We provide our findings and insights on the performance characteristics of microVMs on edge devices. With a much higher degree of isolation capability, microVMs can be an attractive virtualization technique for edge computing environments.
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来源期刊
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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