Random early detection gateways for congestion avoidance
IEEE/ACM Transactions on Networking (TON)
Self-similarity in World Wide Web traffic: evidence and possible causes
IEEE/ACM Transactions on Networking (TON)
Promoting the use of end-to-end congestion control in the Internet
IEEE/ACM Transactions on Networking (TON)
A parameterizable methodology for Internet traffic flow profiling
IEEE Journal on Selected Areas in Communications
New directions in traffic measurement and accounting
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
New directions in traffic measurement and accounting: Focusing on the elephants, ignoring the mice
ACM Transactions on Computer Systems (TOCS)
Fair service for mice in the presence of elephants
Information Processing Letters
Statistical techniques for detecting traffic anomalies through packet header data
IEEE/ACM Transactions on Networking (TON)
Improvement of LRU cache for the detection and control of long-lived high bandwidth flows
Computer Communications
A new algorithm for long flows Statistics—MGCBF
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part IV
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In this paper, we propose a novel approach for identifying long-term high-rate flows at a router. Identifying the long-term high-rate flows allows a router to regulate flows intelligently in times of congestion. We employ a limited amount of state to record the arrivals of packets of individual flows. The state is managed as an LRU cache. The LRU cache self converges to hold only the flows that are high rate. The size of the cache need not depend on the number of flows at the router. We analyze a number of internet packet traces to show the effectiveness of this LRUbased cache. It is shown that this scheme is highly scalable since a few flows contribute a significant fraction of the traffic at a router.