用于容器化云系统负载平衡的资源感知最小忙(RALB)策略

Q2 Computer Science
Zakariyae Bouflous, M. Ouzzif, Khalid Bouragba
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引用次数: 0

摘要

容器是现代云环境中的一项关键技术。与虚拟机相比,它们提供了一种轻量级的方式来打包和部署服务应用程序,并具有独立的处理方法。最先进的容器LB算法没有考虑容器需求和服务器能力之间的有效映射,导致资源浪费和响应时间增加,从而对整体QoS产生负面影响。本文提出了一种新的容器LB算法,称为资源感知最小繁忙(RALB)。RALB不仅考虑了每个节点的当前负载(按照最小连接),还考虑了容器的当前资源需求。从资源的角度来看,它将容器分配给最不繁忙、容量最佳的服务器。作者实现了该算法的原型,仿真结果表明,与随机化算法相比,可以实现更均匀的工作负载分布和更好的资源利用率,从而降低延迟和高可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Resource-Aware Least Busy (RALB) Strategy for Load Balancing in Containerized Cloud Systems
Containers are a key technology in modern cloud environments. They provide a lightweight manner to package and deploy service applications compared to virtual machines, with an isolated processing approach. The state-of-the-art containers LB algorithms do not take into account efficient mapping between container requirements and servers' capabilities, resulting in wastage of resources and increased response time, which negatively impacts the overall QoS. This manuscript proposes a new LB algorithm for containers called resource-aware least busy (RALB). RALB not only considers the current load of each node (as per the least connection) but also takes into account the current resource requirements of containers. It assigns containers to the least busy server with optimal capacity from a resource perspective. The authors implemented a prototype of the algorithm, and simulation results shows that more even distribution of workload and better utilization of resources across the nodes can be achieved, resulting in lower latency and high reliability compared to the randomized algorithm.
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来源期刊
International Journal of Cloud Applications and Computing
International Journal of Cloud Applications and Computing COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
6.40
自引率
0.00%
发文量
58
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