数据中心网络的各种网络拓扑结构及胖树与BCube的分析比较综述

Antonio Cortés Castillo
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引用次数: 1

摘要

云中服务器的指数级增长产生了对专用数据中心的网络拓扑的需求,这意味着服务需求伴随着大量存储和服务质量的可用性,这是在位于DCN的大型服务器群中处理大量数据的基本方面。反过来,对新云服务的需求呈指数级增长,因此DCN面临着与可伸缩性、能源效率、网络拥塞和成本相关的新挑战,这些挑战与体系结构和DCN网络拓扑直接相关。同样,从现有的网络拓扑中,我们提出了一个DCN拓扑。本文对Fat-Tree和BCube两种网络拓扑结构进行了比较,采用了指数型随机流量分布和均匀随机流量分布两种统计函数来比较不同的拓扑类型。这种比较有助于解决数据中心网络基础设施中存在的新业务需求、负载均衡、带宽和节点需求等问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Various Network Topologies and an Analysis Comparative Between Fat-Tree and BCube for a Data Center Network: An Overview
The exponential rise of servers in the cloud generates the need for network topologies for specialized data centers, which means that the service requirements are accompanied by the availability of massive storage and quality of services, essential aspects for handling large volumes of data in large server farms located in the DCN. In turn, the requirements for new cloud services have grown exponentially, so DCNs face new challenges related to scalability, energy efficiency, network congestion, and cost, which are directly associated with the architectures and DCN network topologies. Similarly, from existing network topologies we propose a DCN topology. In this paper, Fat-Tree and BCube network topologies are compared by considering the architectures themselves, the metrics for comparing various topology types, and two statistical functions are used such as the exponential random traffic distribution and uniform random traffic distribution. This type of comparison helps to solve the existing problem regarding the demand for new services, load balance, bandwidth, and node requirements in a DC network infrastructure.
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