Efficient Inter-Datacenter Bulk Transfers with Mixed Completion Time Objectives

TL;DR

This paper presents Iris, an SDN-based scheduler that optimizes inter-datacenter bulk transfers for various completion time objectives by constructing multiple multicast trees to improve transfer times and bandwidth efficiency.

Contribution

The paper introduces a novel multicast-based scheduling approach that adapts to different completion time goals and optimizes network resource usage for inter-datacenter transfers.

Findings

Iris improves completion time objectives by approximately 2.5 times.

The scheduler effectively balances load and minimizes bandwidth consumption.

Simulation and emulation results validate the scheduler's performance improvements.

Abstract

Bulk transfers from one to multiple datacenters can have many different completion time objectives ranging from quickly replicating some $k$ copies to minimizing the time by which the last destination receives a full replica. We design an SDN-style wide-area traffic scheduler that optimizes different completion time objectives for various requests. The scheduler builds, for each bulk transfer, one or more multicast forwarding trees which preferentially use lightly loaded network links. Multiple multicast trees are used per bulk transfer to insulate destinations that have higher available bandwidth and can hence finish quickly from congested destinations. These decisions--how many trees to construct and which receivers to serve using a given tree--result from an optimization problem that minimizes a weighted sum of transfers' completion time objectives and their bandwidth consumption. Results from simulations and emulations on Mininet show that our scheduler, Iris, can improve different completion time objectives by about $2.5\times$.