Abstract in a data center network, accurately classifying flow is the key to optimal schedule
flow. However, the existing classification methods cannot meet the demand of real networks …

This paper deals with classifying flows in data center networks, primarily based on the flows'
volume of traffic and duration. Flows are typically classified as long-lived flow or short-lived …

The processing of big data generated by the Industrial Internet of Things (IIoT) calls for the
support of processing at the edge of the network, as well as at the cloud data centers. The …

Software‐defined network, which separates control plane from the underlying physical
devices, has the advantages of global visibility and high flexibility. Among the most typical …

Traffic management is known to be important to effectively utilize the high bandwidth
provided by datacenters. Recent works have focused on identifying elephant flows and …

The software defined networking (SDN) allows separating control and data plane, which
provides better network management and higher utilization for data center network. Among …

Software defined networking (SDN) provides flexible management for datacenter networks
with the flow-level control. Such the fine-grained management, however, consumes large …

In the data center network, traffic has a distinct heavy-tailed distribution characteristic, with
the minority of throughput-sensitive elephant flows occupy most of the bandwidth and the …

Traffic classification is becoming one of the major applications in the data center networks
with a lot of cloud services. Recent works about software defined networking (SDN) have …

Data center networks include a wide variety of service categories, which leads to a complex
network topology. As a result, the QoS of different service flows cannot be guaranteed. In this …