Guaranteed performance for data-parallel applications is important for both service
providers and cloud data centers that host such services. A job of data-parallel applications …

Link utilization has received extensive attention since data centers become the most
pervasive platform for data-parallel applications. A specific job of such applications involves …

Tasks in a data-parallel job communicate with each other through a number of concurrent
flows, which is described as a coflow. These flows are correlated in the sense that the …

This paper presents D2-CAS, a novel decentralized coflow scheduling system, to minimize
the rate of deadline missed coflow for datacenter networks. To design D2-CAS, we first …

Recently, the abstraction of coflow is introduced to capture the collective data transmission
patterns among modern distributed data-parallel applications. During processing, coflows …

Recently, coflow has been proposed as a new abstraction to capture the communication
patterns in a rich set of data parallel applications in data centers. Coflows effectively model …

Datacenter networks routinely support the data transfers of distributed computing
frameworks in the form of coflows, ie, sets of concurrent flows related to a common task. The …

Flow completion times (FCTs) are critical for many cloud applications. To minimize the
average FCT, recent transport designs, such as pFabric, PASE, and PIAS, approximate the …

Data center networks carry a mix of flows, some with deadlines and some without. Existing
mix-flow transport designs assume prior knowledge of flow sizes, which may not hold in …

Data-parallel applications generate a mix of coflows with and without deadlines. Deadline
coflows are mission-critical and must be completed within deadlines, while the non-deadline …