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陈 丽, 李葆春, 李 波. 关于数据中心网络带宽分配的综述[J]. 计算机科学技术学报, 2014, 29(5): 910-917. DOI: 10.1007/s11390-014-1478-x
引用本文: 陈 丽, 李葆春, 李 波. 关于数据中心网络带宽分配的综述[J]. 计算机科学技术学报, 2014, 29(5): 910-917. DOI: 10.1007/s11390-014-1478-x
Li Chen, Baochun Li, Bo Li. Allocating Bandwidth in Datacenter Networks: A Survey[J]. Journal of Computer Science and Technology, 2014, 29(5): 910-917. DOI: 10.1007/s11390-014-1478-x
Citation: Li Chen, Baochun Li, Bo Li. Allocating Bandwidth in Datacenter Networks: A Survey[J]. Journal of Computer Science and Technology, 2014, 29(5): 910-917. DOI: 10.1007/s11390-014-1478-x

关于数据中心网络带宽分配的综述

Allocating Bandwidth in Datacenter Networks: A Survey

  • 摘要: 在云计算背景下,数据中心,作为其底层架构,已经扮演着越来越重要的角色。云计算的本质决定了数据中心的资源被多个竞争实体所共享,例如多个租户通过租用虚拟机来共享亚马逊的EC2公用云,或者多个如MapReduce的数据并行应用共享谷歌的私有云。在传统的传输层协议分配链路带宽的机制下,多个竞争应用的网络流量互相干扰,使得应用的性能缺少可预测性和公平性。这个重要问题已经引起学术界的广泛关注,一系列关于竞争应用间有效并公平共享数据中心带宽的新策略已经被提出。本文调研了已有文献中关于数据中心带宽分配的机制,涵盖了公有云和私有云的场景。我们详尽地探究了这些策略的设计原则,以及它们在不同选择上的折衷,并将它们总结归纳于一个设计空间,以求能给出有意义的见解,使得未来能有更好的机制出现。

     

    Abstract: Datacenters have played an increasingly essential role as the underlying infrastructure in cloud computing. As implied by the essence of cloud computing, resources in these datacenters are shared by multiple competing entities, which can be either tenants that rent virtual machines (VMs) in a public cloud such as Amazon EC2, or applications that embrace data parallel frameworks like MapReduce in a private cloud maintained by Google. It has been generally observed that with traditional transport-layer protocols allocating link bandwidth in datacenters, network traffic from competing applications interferes with each other, resulting in a severe lack of predictability and fairness of application performance. Such a critical issue has drawn a substantial amount of recent research attention on bandwidth allocation in datacenter networks, with a number of new mechanisms proposed to efficiently and fairly share a datacenter network among competing entities. In this article, we present an extensive survey of existing bandwidth allocation mechanisms in the literature, covering the scenarios of both public and private clouds. We thoroughly investigate their underlying design principles, evaluate the tradeoff involved in their design choices and summarize them in a unified design space, with the hope of conveying some meaningful insights for better designs in the future.

     

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