Oct 1, 2019 · In this paper, we identify large size flows from multiple historical TMs instead of monitoring each flow.

In this paper, we have studied the SDN-based traffic matrix estimation in data center networks through large size flow identification by machine learning.

Software defined networking (SDN) with separated control plane and data plane brings new opportunities for traffic measurement in data center networks.

May 2, 2023 · Directly monitoring each flow and discovering that large size flows consume a massive amount of channel bandwidth resource between control plane ...

Nov 19, 2019 · Accurate traffic matrix estimation is critical to solving many networking problems, such as routing and network provisioning, etc.

In this paper, we seek accurate, feasible and scalable traffic matrix estimation approaches. We propose two strategies, called Maximum Load Rule First (MLRF) ...

In this paper, we propose an intelligent framework for Traffic Matrix (TM) inference in Software Defined Networks (SDN) where the Ternary Content ...

Jun 18, 2015 · The simulation results show that we can find out the real large flows with very high probability by using the estimated per-flow sizes. In ...

The suggested methodology is designed to teach users how to match traffic flows in ways that increase granularity while proactively protecting the SDN data ...

Oct 28, 2022 · The SDN defense system consists of two modules: anomaly detection module and mitigation module. The anomaly detection model uses a lightweight ...