DCCast: Efficient Point to Multipoint Transfers Across Datacenters

TL;DR

DCCast is a centralized algorithm that efficiently distributes data from one datacenter to multiple others using forwarding trees, significantly reducing bandwidth and transfer times in inter-datacenter networks.

Contribution

We introduce DCCast, a novel P2MP algorithm that optimizes data transfer efficiency and load balancing across datacenter networks.

Findings

Reduces total bandwidth usage by up to 50%

Cuts tail transfer completion times by up to 50%

Uses low computational overhead for forwarding tree selection

Abstract

Using multiple datacenters allows for higher availability, load balancing and reduced latency to customers of cloud services. To distribute multiple copies of data, cloud providers depend on inter-datacenter WANs that ought to be used efficiently considering their limited capacity and the ever-increasing data demands. In this paper, we focus on applications that transfer objects from one datacenter to several datacenters over dedicated inter-datacenter networks. We present DCCast, a centralized Point to Multi-Point (P2MP) algorithm that uses forwarding trees to efficiently deliver an object from a source datacenter to required destination datacenters. With low computational overhead, DCCast selects forwarding trees that minimize bandwidth usage and balance load across all links. With simulation experiments on Google's GScale network, we show that DCCast can reduce total bandwidth usage and tail Transfer Completion Times (TCT) by up to $50\%$ compared to delivering the same objects via independent point-to-point (P2P) transfers.