一种基于平衡排队网络的多业务应用整体自缩放算法

Jing-hua Tong, M. Wei, Maolin Pan, Yang Yu
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引用次数: 6

摘要

容器支持的微服务技术在云应用中得到了广泛的应用。对于弹性云,通过自动伸缩技术将应用程序响应时间维持在服务水平协议(SLA)内是至关重要的。对于由多个服务组成的应用(即多服务应用),由于拓扑结构复杂,降低自伸缩算法性能的因素很多,如服务之间的相关性、决策不及时、供过于求等。为了解决这个问题,我们提出了一种基于均衡Jackson排队网络(JQN)的整体自动缩放算法(HAB),以更少的资源成本快速减少SLA违规。通过整体自动扩展策略,HAB可以快速准确地扩展所有服务。HAB保持了服务间的平衡状态,节省了资源成本,减少了自伸缩决策空间,简化了算法参数。实验结果表明,与其他主要方法相比,HAB算法的SLA违规率平均降低42.31%,资源成本平均降低17.88%,稳定性平均提高19.39%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Holistic Auto-Scaling Algorithm for Multi-Service Applications Based on Balanced Queuing Network
Container-supported microservice technology is widely used in cloud applications. For elastic cloud, it's vital to maintain application response time within service-level agreements (SLA) by auto-scaling technology. For applications composed of multiple services (i.e. multi-service applications), due to complex topologies, there are many factors that reduce auto-scaling algorithm performance, such as correlations among services, untimely decision, oversupply, etc. To resolve this, we propose a holistic auto-scaling algorithm (HAB) based on balanced Jackson queuing network (JQN) to reduce SLA violations rapidly with less resource cost. With the holistic auto-scaling strategy, HAB scales all services quickly and accurately. Keeping the balanced state among services, HAB saves resource cost, reduces auto-scaling decision space and simplifies algorithm parameters. The experimental results demonstrate that HAB has an average decrease of 42.31% in SLA violation rate, an average decrease of 17.88% in resource cost and an average increase of 19.39% in stability, compared with other main methods.
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