多租户环境下qos感知负载均衡策略

Hailong Sun, Tao Zhao, Yu Tang, Xudong Liu
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引用次数: 6

摘要

云计算旨在基于共享的基础资源池提供服务,负载平衡在这种环境中至关重要。同时,在云计算中广泛采用多租户,以降低服务提供成本,提高资源利用率。多租户带来了资源竞争和托管应用对QoS的不同要求,给负载平衡带来了新的挑战。因此,部署了多个应用程序的服务器需要适当的请求调度策略来保证其服务质量,例如响应时间。然而,大多数qos感知负载平衡算法并不关心部署在同一服务器上的应用程序之间的相互干预。在高负载下,某些应用程序的平均响应时间可能会变得太高而无法接受。本文提出了一种基于M/G/s/s+r队列模型的新的负载均衡算法“服务器吞吐量限制(STR)”,以保证每个应用程序的平均响应时间,并获得更好的服务器吞吐量。此外,我们还进行了几个实验来分析STR与轮循和最少剩余工作的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A QoS-Aware Load Balancing Policy in Multi-tenancy Environment
Cloud computing aims at providing services on the basis of a shared pool of underpinning resources and load balancing is of paramount importance in such an environment. At the same time, multi-tenancy is widely adopted in cloud computing to reduce the costs of service provisioning and to improve resource utilization. Multi-tenancy brings new challenges to load balancing, since it incurs resource competition and different QoS requirements of hosted applications. Therefore, servers with multiple deployed applications need a proper request scheduling policy to guarantee their quality of service, e.g., response time. However, most of the QoS-aware load balancing algorithms do not concern about the mutual intervention among applications deployed on the same server. When under heavy loads, mean response time of some applications may become too high to be acceptable. In this work, we propose a new load balancing algorithm, "Server Throughput Restriction(STR)", based on M/G/s/s+r queueing model, in order to guarantee each application's mean response time and also achieve better server throughput. In addition, we conduct several experiments to analyze the performance of STR in comparison with Round-Robin and Least-Work-Remaining.
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