基于笼图的边缘数据中心组织与优化

IF 3.6 3区 医学 Q2 NEUROSCIENCES
P. Roig, S. Alcaraz, K. Gilly, Cristina Bernad, C. Juiz
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引用次数: 1

摘要

由于边缘计算和雾计算设施的部署不断增长,数据中心的组织和优化越来越受到关注。其主要目标是实现一种拓扑结构,该拓扑不仅依赖于基于人工智能的计算资源,而且依赖于物理主机之间的网络互连。本文介绍了图论,由于其与网络连接性和稳定性相关的特性,这导致了更有弹性和可持续的部署,其中笼图可能比其他图具有优势。在这种情况下,Petersen图笼由于其节点数量少,网络直径小,被研究为小型数据中心的方便候选者,从而为边缘和雾数据中心提供了一个有趣的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Edge Data Center Organization and Optimization by Using Cage Graphs
Data center organization and optimization are increasingly receiving attention due to the ever-growing deployments of edge and fog computing facilities. The main aim is to achieve a topology that processes the traffic flows as fast as possible and that does not only depend on AI-based computing resources, but also on the network interconnection among physical hosts. In this paper, graph theory is introduced, due to its features related to network connectivity and stability, which leads to more resilient and sustainable deployments, where cage graphs may have an advantage over the rest. In this context, the Petersen graph cage is studied as a convenient candidate for small data centers due to its small number of nodes and small network diameter, thus providing an interesting solution for edge and fog data centers.
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来源期刊
Network Neuroscience
Network Neuroscience NEUROSCIENCES-
CiteScore
6.40
自引率
6.40%
发文量
68
审稿时长
16 weeks
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