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Impact of Instance Seeking Strategies on Resource Allocation in Cloud Data Centers

机译:实例搜索策略对云数据中心资源分配的影响

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With the prosperity of cloud computing, an increasing number of Small and Medium-sized Enterprises (SMEs) move their business to public clouds such as Amazon EC2. To help tenants deploy services in the cloud, researchers either conduct performance evaluations or design mechanisms and software on seeking virtual machines of better performance. However, few studies have investigated the impact of instance seeking strategies on resource allocation in clouds if every tenant starts to apply the same method to find the better-performing virtual machine. In this paper, we propose a cloud and a tenant model in order to simulate the process of tenants' seeking better-performing instances in the cloud. We discuss, implement and evaluate six cloud resource allocation strategies and five instance seeking strategies. We perform the evaluation via simulation based on real data traces. Our results show that instance seeking strategies can cause the exhaustion of better-performing instances and significant request growth in the cloud. Furthermore, we find that tenants could save time and budget through collaborative seeking strategies. Finally, we discuss the implications of our findings from perspectives of both tenants and providers.
机译:随着云计算的繁荣,越来越多的中小企业(SME)将其业务转移到诸如Amazon EC2之类的公共云。为了帮助租户在云中部署服务,研究人员可以进行性能评估或设计机制和软件,以寻求性能更好的虚拟机。但是,如果每个租户都开始使用相同的方法来查找性能更好的虚拟机,则很少有研究调查实例搜索策略对云中资源分配的影响。在本文中,我们提出了云和租户模型,以模拟租户在云中寻找性能更好的实例的过程。我们讨论,实施和评估六种云资源分配策略和五种实例搜索策略。我们通过基于真实数据轨迹的模拟进行评估。我们的结果表明,实例搜索策略可能会导致性能更佳的实例用尽,并导致云中的请求显着增长。此外,我们发现租户可以通过协作寻求策略来节省时间和预算。最后,我们从租户和提供者的角度讨论研究结果的含义。

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