A DAG-Based Network Traffic Scheduler

Nowadays, it is common that distributed jobs within a datacenter compete for different resources, especially the network. Due to this competition, these jobs’ performance is decreased and datacenters run at low efficiency. Most previous work on network scheduling lacks the knowledge of detailed requirements of jobs, hence the scheduling benefit is limited. In this paper, we try to develop a new scheduling algorithm which aims at reducing the job completion time (JCT). To achieve this goal, we take advantage of the directed acyclic graph (DAG) to build a novel network scheduler. The proposed scheduler formulates the problem as an integer linear programming (ILP) model, and proves it can be solved through an equivalent linear programming (LP) model quickly. Finally, experimental results demonstrate that our scheduler can return the solution in a few seconds and accelerate jobs significantly.