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A scalable approach for structuring large-scale hierarchical cloud management systems

机译:一种结构化大规模分层云管理系统的可扩展方法

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In recent years, the scale of clouds and networks has increased greatly. It is important to ensure that the management systems used in these environments can scale as well. A centralized system does not scale well, while for distributed approaches, it is difficult to maintain an overview of the global system state. In hierarchical management systems, nodes at a low level in the hierarchy have a detailed view of a small part of the network, while higher-level nodes have a less detailed view of larger parts of the network. This makes hierarchical management systems well suited for large scale systems. The structure of such a hierarchical system should however be impacted by the management system for which it is used, as various properties such as the number of child nodes, tree depth and the distance between nodes can impact the performance of the management system. In this paper, we describe the Scalable Hierarchical Management Framework (SHMF), a scalable approach for constructing a hierarchical management system, suitable for large-scale cloud environments, that automatically optimizes its structure in function of its overlying management system. We evaluate the approach based on the requirements for the cloud application placement problem.
机译:近年来,云和网络的规模大大增加。重要的是要确保在这些环境中使用的管理系统也可以扩展。对于分布式方法,集中式系统不符合速度良好,而难以保持全球系统状态的概述。在分层管理系统中,层次结构中的低电平的节点具有网络的一小部分的详细视图,而更高级别的节点具有较少的网络较大部分的详细视图。这使得等级管理系统适合大规模系统。然而,这种分层系统的结构应受到其使用的管理系统的影响,因为诸如子节点的数量,树深度和节点之间的距离可能影响管理系统的性能。在本文中,我们描述了可扩展的分层管理框架(SHMF),一种可扩展方法,用于构造一个适用于大规模云环境的分层管理系统,它可以在其覆盖管理系统的功能中自动优化其结构。根据云应用程序放置问题的要求,我们评估方法。

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