C4.5: programs for machine learning
C4.5: programs for machine learning
Fast and scalable layer four switching
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication
High-speed policy-based packet forwarding using efficient multi-dimensional range matching
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication
Packet classification using tuple space search
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Scalable packet classification
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
Introduction to Algorithms
Packet classification using multidimensional cutting
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Transport layer identification of P2P traffic
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
BLINC: multilevel traffic classification in the dark
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
Survey and taxonomy of packet classification techniques
ACM Computing Surveys (CSUR)
Traffic classification on the fly
ACM SIGCOMM Computer Communication Review
ACM SIGCOMM Computer Communication Review
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
DPICO: a high speed deep packet inspection engine using compact finite automata
Proceedings of the 3rd ACM/IEEE Symposium on Architecture for networking and communications systems
A survey of techniques for internet traffic classification using machine learning
IEEE Communications Surveys & Tutorials
Algorithms for packet classification
IEEE Network: The Magazine of Global Internetworking
Large-scale wire-speed packet classification on FPGAs
Proceedings of the ACM/SIGDA international symposium on Field programmable gate arrays
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
ACM Transactions on Architecture and Code Optimization (TACO) - Special Issue on High-Performance Embedded Architectures and Compilers
High throughput and programmable online trafficclassifier on FPGA
Proceedings of the ACM/SIGDA international symposium on Field programmable gate arrays
Scalable packet classification on FPGA
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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Traffic classification remains a hot research problem, especially when facing new traffic trends and new hardware architectures. We propose a classification tree search method called explicit range search, motivated by the characteristics of machine learning based classification approaches. Our method differs from previously known algorithms such as HiCut and HyperCut in how to cut the ranges within a dimension and how to search within the ranges. By storing explicit marks and performing hardware supported parallel comparison, the explicit range search can reduce the worst-case number of memory accesses from 26 to 5 on a number of realistic rule sets generated from a well-known machine learning algorithm (C4.5). We also describe in this paper the proposed design based on FPGA devices.