TY - GEN
T1 - Scaling IP multicast on datacenter topologies
AU - Li, Xiaozhou
AU - Freedman, Michael J.
N1 - Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - IP multicast would reduce significantly both network and server overhead for many datacenter applications' communication. Unfortunately, traditional protocols for managing IP multicast, designed for arbitrary network topologies, do not scale with aggregate hardware resources in the number of supported multicast groups. Prior attempts to scale multicast in general settings are all bottlenecked by the forwarding table capacity of a single switch. This paper shows how to leverage the unique topological structure of modern datacenter networks in order to build the first scale-out multicast architecture. In our architecture, a network controller carefully partitions the multicast address space and assigns the partitions across switches in datacenters' multi-rooted tree networks. Our approach further improves scalability by locally aggregating multicast addresses at bottleneck switches that are running out of forwarding table space, at the cost of slightly inflating downstream traffic. We evaluate the system's scalability, traffic overhead, and fault tolerance through a mix of simulation and analysis. For example, experiments show that a datacenter with 27,648 servers and commodity switches with 1000-entry multicast tables can support up to 100,000 multicast groups, allowing each server to subscribe to nearly 200 multicast groups concurrently.
AB - IP multicast would reduce significantly both network and server overhead for many datacenter applications' communication. Unfortunately, traditional protocols for managing IP multicast, designed for arbitrary network topologies, do not scale with aggregate hardware resources in the number of supported multicast groups. Prior attempts to scale multicast in general settings are all bottlenecked by the forwarding table capacity of a single switch. This paper shows how to leverage the unique topological structure of modern datacenter networks in order to build the first scale-out multicast architecture. In our architecture, a network controller carefully partitions the multicast address space and assigns the partitions across switches in datacenters' multi-rooted tree networks. Our approach further improves scalability by locally aggregating multicast addresses at bottleneck switches that are running out of forwarding table space, at the cost of slightly inflating downstream traffic. We evaluate the system's scalability, traffic overhead, and fault tolerance through a mix of simulation and analysis. For example, experiments show that a datacenter with 27,648 servers and commodity switches with 1000-entry multicast tables can support up to 100,000 multicast groups, allowing each server to subscribe to nearly 200 multicast groups concurrently.
KW - Datacenter networks
KW - IP multicast
KW - Scalability
UR - http://www.scopus.com/inward/record.url?scp=84893347759&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84893347759&partnerID=8YFLogxK
U2 - 10.1145/2535372.2535380
DO - 10.1145/2535372.2535380
M3 - Conference contribution
AN - SCOPUS:84893347759
SN - 9781450321013
T3 - CoNEXT 2013 - Proceedings of the 2013 ACM International Conference on Emerging Networking Experiments and Technologies
SP - 61
EP - 72
BT - CoNEXT 2013 - Proceedings of the 2013 ACM International Conference on Emerging Networking Experiments and Technologies
PB - Association for Computing Machinery
T2 - 2013 9th ACM International Conference on Emerging Networking Experiments and Technologies, CoNEXT 2013
Y2 - 9 December 2013 through 12 December 2013
ER -