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Mechanisms for building autonomically scalable services on cooperatively shared computing platforms

机译:在协作共享计算平台上构建可自动扩展的服务的机制

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We present here a system architecture and its underlying mechanisms for building autonomically scalable and resilient services on cooperatively shared computing platforms. Specifically, our focus is on utilizing computing platforms exhibiting the following characteristics. The resources at a node in such platforms are allocated to competing users on fair-share basis, without any reserved resource capacities for any user. There is no platform-wide resource manager for the placement of users on different nodes. The users independently select nodes for their applications. Moreover, a node can become unavailable at any time due to crashes or shutdowns. Building scalable services in such environments poses unique challenges due to node-level fluctuations in the available resource capacities and node crashes. The service load may surge in a short time due to flash crowds. Autonomic scaling of service capacity is performed by dynamic control of the degree of service replication based on the estimated service capacity and the observed load. We present here models for estimating the service capacity at a node under fluctuating operating conditions. Furthermore, we develop adaptive and agile load distribution mechanisms for distributing load among replicas based on their time-varying service capacities. We present the results of our evaluations of these mechanisms on PlanetLab, which exemplifies the platform level characteristics considered here.
机译:我们在这里介绍了一种用于在协作共享的计算平台上构建可自动扩展和弹性服务的系统体系结构及其底层机制。具体来说,我们的重点是利用具有以下特征的计算平台。在此类平台中,将节点上的资源按公平份额分配给竞争用户,而没有为任何用户保留任何资源容量。没有用于将用户放置在不同节点上的平台范围的资源管理器。用户独立为其应用选择节点。此外,由于崩溃或关闭,节点随时可能变得不可用。由于可用资源容量中的节点级波动和节点崩溃,在这样的环境中构建可伸缩服务提出了独特的挑战。由于闪存拥挤,服务负载可能会在短时间内激增。通过根据估计的服务容量和观察到的负载对服务复制程度进行动态控制,可以自动调整服务容量。我们在这里提出模型,用于估计在波动的工作条件下节点的服务容量。此外,我们开发了自适应且敏捷的负载分配机制,用于根据副本的时变服务容量在副本之间分配负载。我们在PlanetLab上介绍了对这些机制的评估结果,这些评估例证了此处考虑的平台级别特征。

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