Deadline-Aware Scheduling and Routing for Inter-Datacenter Multicast Transfers

Many applications like geo-replication need to deliver multiple copies of data from a single datacenter to multiple datacenters, which has benefits of improving fault tolerance, increasing availability and achieving high service quality. These applications usually require completing multicast transfers before certain deadlines. Some of the existing works only consider unicast transfers, which is not appropriate for the multicast transmission type. An alternative approach proposed by existing works was to find a minimum weight Steiner tree for each transfer. Instead of using only one tree for each transfer, we propose to use one or multiple trees, which increases the flexibility of routing, improves the utilization of available bandwidth, and increases the throughput for each transfer. In this paper, we focus on the multicast transmission type, propose an efficient and effective solution that maximizes throughput for all transfer requests while meeting deadlines. We also show that our solution can reduce packet reordering by selecting very few Steiner trees for each transfer. We have implemented our solution on a software-defined overlay network at the application layer, and our real-world experiments on the Google Cloud Platform have shown that our system effectively improves the network throughput performance and has a lower traffic rejection rate compared to existing related works.