Tracking Per-Flow State – Binned Duration Flow Tracking
Brad Whitehead, Chung–Horng Lung, Peter Rabinovitch · Journal of Networks · 2012
Recent advances in network monitoring have increasingly focused on obtaining per-flow information, such as flow state. Tracking the state of network flows opens up a new dimension of information gathering for network operators, allowing previously unattainable data to be captured. This paper presents a time efficient novel method — Binned Duration Flow Tracking (BDFT) — of tracking per-flow state by grouping valid flows into “bins”. BDFT is intended for high-speed routers where CPU time is crucial. BDFT is time efficient by adopting Bloom filters as the primary data structures. Simulation results show that BDFT can achieve over 99% accuracy on traces of real network traffic.