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Decentralized Self-Adaptive Computing at the Edge

机译:边缘的分散式自适应计算

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摘要

Nowadays, computing infrastructures are usually deployed in fully controlled environments and managed in a centralized fashion. Leveraging on centralized infrastructures prevent the system to deal with scalability and performance issues, which are inherent to modern large-scale data-intensive applications. On the other hand, we envision fully decentralized computing infrastructures deployed at the edge of the network providing the required support for operating data-intensive systems. However, engineering such systems raises many challenges, as decentralization introduces uncertainty, which in turn may harm the dependability of the system. To this end, self-adaptation is a key approach to manage uncertainties at runtime and satisfy the requirements of decentralized data-intensive systems. This paper shows the research directions and current contributions towards this vision by (i) evaluating the impact of the distribution of computational entities, (ii) engineering decentralized computing through self-adaptation and, (iii) evaluating decentralized and self-adaptive applications.
机译:如今,计算基础结构通常部署在完全受控的环境中,并以集中方式进行管理。利用集中式基础架构会阻止系统处理可伸缩性和性能问题,这是现代大规模数据密集型应用程序固有的。另一方面,我们设想在网络边缘部署完全分散的计算基础架构,为运行数据密集型系统提供所需的支持。然而,工程设计这样的系统提出了许多挑战,因为分散会带来不确定性,这又可能损害系统的可靠性。为此,自适应是一种在运行时管理不确定性并满足分散数据密集型系统要求的关键方法。本文通过(i)评估计算实体分布的影响,(ii)通过自适应进行工程去中心化计算,以及(iii)评估去中心化和自适应应用程序,显示了该愿景的研究方向和当前贡献。

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