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Packet classification based on the decision tree with information entropy

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Abstract

Packet classification is indispensable for the next-generation routers targeting at the complete integration of advanced networking capabilities, which include differentiated services, memory access control, policy routing, and traffic billing. The classification method based on decision tree is advantageous in its structure and high efficiency, so it is suitable for real-time packet classification. A heuristic method is proposed based on the information entropy to build the decision tree more balanced considering the time complexity and the space complexity. It is suitable to solve rule subset uneven phenomenon and meets the requirement of big data with diverse data formats. The simulation results show that the algorithm can classify the packets quickly compared with previously described algorithms and has relatively small storage requirements.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Nos. 61763048, 61263022, 61303234), Science and Technology Foundation of Yunan Province (No. 2017FB095), the 18th Yunnan Young and Middle-aged Academic and Technical Leaders Reserve Personnel Training Program (No. 2015HB038), the key research project of natural science of Anhui Provincial Department of Education (KJ2017A354). The authors would like to thank the anonymous reviewers and the editors for their helpful suggestions and comments.

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Authors and Affiliations

  1. School of Computer and Information, Anqing Normal University, Anqing, Anhui, 246011, China

    Xiaoming Dong & Meng Qian

  2. School of Information, Yunnan University of Finance and Economics, Kunming, 650221, China

    Rong Jiang

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  1. Xiaoming Dong
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  2. Meng Qian
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  3. Rong Jiang
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Contributions

XD and RJ designed the experiments and wrote the paper; MQ contributed the simulation experiments; All authors have read and approved the final manuscript.

Corresponding author

Correspondence to Rong Jiang.

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Dong, X., Qian, M. & Jiang, R. Packet classification based on the decision tree with information entropy. J Supercomput 76, 4117–4131 (2020). https://doi.org/10.1007/s11227-017-2227-z

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