TY - GEN
T1 - Duo
T2 - 2023 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2023
AU - Zerwas, Johannes
AU - Györgyi, Csaba
AU - Blenk, Andreas
AU - Schmid, Stefan
AU - Avin, Chen
N1 - Publisher Copyright:
© 2023 Owner/Author.
PY - 2023/6/19
Y1 - 2023/6/19
N2 - 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 \system's control and data plane.
AB - 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 \system's control and data plane.
KW - datacenter networks
KW - demand-Aware
KW - network design
KW - optical networks
UR - http://www.scopus.com/inward/record.url?scp=85146950429&partnerID=8YFLogxK
U2 - 10.1145/3578338.3593537
DO - 10.1145/3578338.3593537
M3 - Conference contribution
AN - SCOPUS:85146950429
T3 - SIGMETRICS 2023 - Abstract Proceedings of the 2023 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems
SP - 7
EP - 8
BT - SIGMETRICS 2023 - Abstract Proceedings of the 2023 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems
PB - Association for Computing Machinery, Inc
Y2 - 19 June 2023 through 23 June 2023
ER -