Duo: A High-Throughput Reconfigurable Datacenter Network Using Local Routing and Control

Author:

Zerwas Johannes1ORCID,Györgyi Csaba2ORCID,Blenk Andreas3ORCID,Schmid Stefan4ORCID,Avin Chen5ORCID

Affiliation:

1. Technical University of Munich, Munich, Germany

2. ELTE Eötvös Loránd University & University of Vienna, Budapest, Hungary

3. Siemens AG, Munich, Germany

4. TU Berlin & Fraunhofer SIT, Berlin, Germany

5. Ben Gurion University of the Negev, Beer-Sheva, Israel

Abstract

The performance of many cloud-based applications critically depends on the capacity of the underlying datacenter network. A particularly innovative approach to improve the throughput in datacenters is enabled by emerging optical technologies, which allow to dynamically adjust the physical network topology, both in an oblivious or demand-aware manner. However, such topology engineering, i.e., the operation and control of dynamic datacenter networks, is considered complex and currently comes with restrictions and overheads. We present Duo, a novel demand-aware reconfigurable rack-to-rack datacenter network design realized with a simple and efficient control plane. Duo is based on the well-known de Bruijn topology (implemented using a small number of optical circuit switches) and the key observation that this topology can be enhanced using dynamic (''opportunistic'') links between its nodes. In contrast to previous systems, Duo has several desired features: i) It makes effective use of the network capacity by supporting integrated and multi-hop routing (paths that combine both static and dynamic links). ii) It uses a work-conserving queue scheduling which enables out-of-the-box TCP support. iii) Duo employs greedy routing that is implemented using standard IP longest prefix match with small forwarding tables. And iv) during topological reconfigurations, routing tables require only local updates, making this approach ideal for dynamic networks. We evaluate Duo in end-to-end packet-level simulations, comparing it to the state-of-the-art static and dynamic networks designs. We show that Duo provides higher throughput, shorter paths, lower flow completion times for high priority flows, and minimal packet reordering, all using existing network and transport layer protocols. We also report on a proof-of-concept implementation of Duo's control and data plane.

Funder

European Research Council

Deutsche Forschungsgemeinschaft

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Safety, Risk, Reliability and Quality,Computer Science (miscellaneous)

Reference56 articles.

1. Vamsi Addanki , Chen Avin , and Stefan Schmid . 2023 . Mars: Near-Optimal Throughput with Shallow Buffers in Reconfigurable Datacenter Networks. In ACM SIGMETRICS (accepted). Vamsi Addanki, Chen Avin, and Stefan Schmid. 2023. Mars: Near-Optimal Throughput with Shallow Buffers in Reconfigurable Datacenter Networks. In ACM SIGMETRICS (accepted).

2. A scalable, commodity data center network architecture

3. Data center TCP (DCTCP)

4. On the Complexity of Traffic Traces and Implications

5. Toward demand-aware networking

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Towards real-time non-preemptive multicast scheduling in reconfigurable data center networks;Peer-to-Peer Networking and Applications;2024-09-12

2. Optimizing Reconfigurable Optical Datacenters: The Power of Randomization;Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis;2023-11-11

3. FactoryDC: Network and Resource Planning for Emerging Applications in Future Factories;Proceedings of the 1st Workshop on Enhanced Network Techniques and Technologies for the Industrial IoT to Cloud Continuum;2023-09-10

4. Duo: A High-Throughput Reconfigurable Datacenter Network Using Local Routing and Control;ACM SIGMETRICS Performance Evaluation Review;2023-06-26

5. Duo: A High-Throughput Reconfigurable Datacenter Network Using Local Routing and Control;Abstract Proceedings of the 2023 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems;2023-06-19

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3