  In the past decade, increasingly network scheduling techniques have been
proposed to boost the distributed application performance. Flow-level metrics,
such as flow completion time (FCT), are based on the abstraction of flows yet
they cannot capture the semantics of communication in a cluster application.
Being aware of this problem, coflow is proposed as a new network abstraction.
However, it is insufficient to reveal the dependencies between computation and
communication. As a result, the real application performance can be hurt,
especially in the absence of hard barriers. Based on the computation DAG of the
application, we propose an expressive abstraction namely metaflow that resides
in the middle of the two extreme points of flows and coflows. Evaluation
results show that metaflow-based scheduling can outperform the coflow-based
algorithm by 1.78x.
