Ingredients to enhance the performance of two-stage TCAM-based packet classifiers in internet of things: greedy layering, bit auctioning and range encoding-Reference-Cited by-同舟云学术

Ingredients to enhance the performance of two-stage TCAM-based packet classifiers in internet of things: greedy layering, bit auctioning and range encoding

Published:2019-12 Issue:1 Volume:2019 Page:
ISSN:1687-1499
Container-title:EURASIP Journal on Wireless Communications and Networking
language:en
Short-container-title:J Wireless Com Network

Author:

Abbasi Mahdi^ORCID,Vakilian Shakoor,Fanian Ali,Khosravi Mohammad R.

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Computer Science Applications,Signal Processing

Link

http://link.springer.com/content/pdf/10.1186/s13638-019-1617-8.pdf

Reference48 articles.

1. B. Indira, K. Valarmathi, D. Devaraj, An approach to enhance packet classification performance of software-defined network using deep learning. Soft Computing 23(18), 8609–8619 (2019)

2. J. Wee, J.-G. Choi, W. Pak, Wildcard fields-based partitioning for fast and scalable packet classification in vehicle-to-everything. Sensors 19(11), 2563 (2019)

3. S.R. Hussain, S. Nirjon, E. Bertino, in 2019 15th International Conference on Distributed Computing in Sensor Systems (DCOSS). Securing the insecure link of Internet-of-Things using next-generation smart gateways (IEEE, 2019)

4. E. Hodo et al., in 2016 International Symposium on Networks, Computers and Communications (ISNCC). Threat analysis of IoT networks using artificial neural network intrusion detection system (IEEE, 2016)

5. A. Sivanathan et al., Characterizing and classifying IoT traffic in smart cities and campuses. in 2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). 2017. IEEE.

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