Oversubscription Bounded Multicast Scheduling in Fat-Tree Data Center Networks

Abstract

Multicast benefits numerous data center applications that require group communication by eliminating sending unnecessary duplicated packets in the network, thus significantly reduces network traffic and improves application throughput. Meanwhile, many data center networks (DCNs) adopt a multi-rooted tree structure called fat-tree, which utilizes rich path multiplicity to deliver high bisection bandwidth. However, currently there is no efficient flow scheduling algorithm for the fat-tree that can route multicast flows appropriately to achieve traffic load balance, thus cannot fully take advantage of this high degree of link parallelism. Besides low bandwidth utilization, unbalanced traffic load distribution also leads to unpredictable network performance and degraded data center agility. In this paper, we study multicast traffic load balance problem in fat-tree DCNs. First, we derive a minimum link oversubscription upper bound in multicast fat-tree DCNs based on a network model that accurately describes the DCN communication environment. Then, we present Oversubscription Bounded Multicast Scheduling (OBMS), a low-complexity multicast flow scheduling algorithm that guarantees bounded link oversubscription and efficient network utilization even under the most congested traffic patterns. Finally, we evaluate the performance of OBMS in an event-driven DCN simulator under various types of traffic patterns, and show that OBMS significantly outperforms other load-balance methods in terms of network throughput and evenness of traffic load distribution.