Achieving Efficient Routing in Reconfigurable DCNs

Zhenjie Yang, Yong Cui, Shihan Xiao, Xin Wang, Minming Li, Chuming Li, Yadong Liu
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引用次数: 2

Abstract

With the fast growth of cloud services and network scales, the heavy and highly dynamic traffic demands pose great challenges to the efficient traffic engineering in today's data center networks (DCNs) [21]. The DCN flows can be broadly classified into two main categories: delay-sensitive small flows (e.g., queries or realtime small messages) and throughput-sensitive large flows (e.g., the backup traffic). In general, more than 80% flows in data centers are small flows, while the majority of the traffic volume is contributed by the top 10% large flows [3, 7]. To handle the mixed traffic, today's data centers [1, 14] generally follow the tree-based topologies (e.g., fat-tree) and take the load-agnostic routing strategies based on random path selection (e.g., ECMP1) [14, 19]. Although it is applicable for routing small flows which are highly random, these strategies are likely to route several large flows through the same output link and lead to long-lived congestions [2, 8]. With the limited switch buffer occupied by large flows for a long time, small flows are reported to experience one order of magnitude larger delay, which compromises the performance of DCNs and makes the users suffer [3].
在可重构dcn中实现高效路由
随着云服务和网络规模的快速增长,海量、高动态的流量需求对当今数据中心网络(DCNs)的高效流量工程提出了巨大挑战[21]。DCN流可以大致分为两大类:延迟敏感的小流(例如,查询或实时小消息)和吞吐量敏感的大流(例如,备份流量)。一般来说,数据中心80%以上的流量是小流量,而大部分流量是由前10%的大流量贡献的[3,7]。为了处理混合流量,当今的数据中心[1,14]通常遵循基于树的拓扑(如胖树),并采用基于随机路径选择的负载不可知路由策略(如ECMP1)[14,19]。虽然它适用于路由高度随机的小流,但这些策略很可能通过相同的输出链路路由几个大流,并导致长时间的拥塞[2,8]。由于大流量长时间占用有限开关缓冲区,据报道,小流量的延迟要大一个数量级,这会影响DCNs的性能,让用户感到痛苦[3]。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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