Abstract
The performance of network equipments, such as firewall, router, etc., is decided by the efficiency of patch matching. It is difficult to adapt the speed of packet matching with packets linear forwarding by traditional algorithms. The purpose of this paper is to develop a novel algorithm of packet matching based on improving differential evolutionary algorithm, which also combines with classic packets matching algorithms to improve the performance of algorithm. For the sake of objectivity, the statistics method was used to compute the fitting value. Experiments showed that this new algorithm effectively improved the performance in the speed and storage space, as compared with the traditional one. For the first time, evolutionary algorithm is used to solve the network data packet forwarding, and packets can be forwarded at the linear speed. In addition, this new algorithm is universal, so it can be adapted for many equipment.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
El-Atawy A, Chincago Samak T, Al-Shaer E, et al. Using online traffic statisticalmatching for optimizing packet filtering performance [C]//Proceedings of the 26th IEEE International Conference on Computer Communications. Anchorage: IEEE Press, 2007: 866–874.
Hari A, Suri S, Parulkar G. Detecting and resolving packet filter conflicts [C]//Proceedings of the 19th IEEE International Conference on Computer Communications. San Francisco: IEEE Press, 2000: 1203–1212.
El-Atawy A, Hamed H, Al-Shaer E. Adaptive statistical optimization techniques for firewall packet filtering [C]//Proceedings of IEEE Infocom. Chicago: IEEE Press, 2006: 1101–1120.
Kencl L, Schwarzer C. Traffic-adaptive packet filtering of denial of service attacks [C]//Proceedings of the 2006 International Symposium on World of Wireless, Mobile and Multimedia Networks. Washington D C: IEEE Press, 2006: 485–489.
McAulay A J, Francis P. Fast routing table lookup using CAMs [C]//Proceedings of the 12th IEEE International Conference on Computer Communications, March. San Francisco: IEEE Press, 1993: 1382–1391.
Acharya S, Abliz M, Mills B, et al. OPTWALL: A hierarchical traffic-aware firewall optimization [C]//Proceedings of the Network and Distributed Systems Symposium. San Diego: IEEE Press, 2007: 528–533.
Woo T Y C. Bell Labs, Lucent Technol. A modular approach to packet classification:algorithm and results [C]// Gruein R ed. Proceedings of IEEE Infocom 2000. San Francisco: IEEE Press, 2000: 1210–1217.
Warkhede P, Suri S, Varghese G. Fast packet classification for two-dimensional conflict-free filters [C]//Proceedings of Twentieth Annual Joint Conference of the IEEE Computer and Communications Societies. Anchorage: IEEE Press, 2001: 1434–1443.
Srinivasan V, Varghese G, Suri S, et al. Fast and scalable layer 4 switching [C]//Proc of ACM Sigcomm. New York: ACM Press, 1998.
Beboescu F, Singh S, Varghese G. Packet classification for core routers:Is there an alternative to CAMs? [C]// Proceedings of the 22th IEEE International Conference on Computer Communications. San Diego: IEEE Press, 2003: 53–63.
Buddhikot M, Suri S, Waldvogel M. Space decomposition techniques for fast layer-4 switching [C]//Proceedings of Conference on Protocols for High Speed Networks. Salem: IEEE Press, 1999: 25–41.
Feldman A, Muthukrishnan S. Tradeoffs for packet classification [C]//Proceedings of the 12th IEEE International Conference on Computer Communications. Tel Aviv: IEEE Press, 2000, 3: 1193–1202.
Gupta P, McKeown N. Packet classification using hierarchical intelligent cuttings [C]//Proceedings of ACM SIGCOMM 1999. New York: ACM Press, 1999: 147–160.
Singh S, Baboescu F, Varghese G, et al. Packet classification using multi-dimensional cutting [C]//Proceedings of the 2003 Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications. New York: ACM Press, 2003: 213–224.
Gupta P, Mckeown N. Packet classification on multiple fields [C]//SIGCOMM’ 99 Proceedings of the Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication. New York: ACM Press, 1999, 29(4): 147–160.
Padhy N P. Artificial Intelligence and Intelligent Systems [M]. Oxford: Oxford University Press, 2005.
Holland J H. Adaptation in Natural and Artificial Systems [M]. Michigan: Univ of Michigan Press, 1975.
Walid A Salameh. Detection of intrusion using neural networks—a customized study [J]. Studies in Information and Control, 2004, 13(2): 135–143.
Wang Xiaoping, Cao Liming. Genetic Algorithm—the Theory, Application and Software Implementation [M]. Xi’an: Xi’an Jiao Tong University Press, 2002(Ch).
Yao Xin, Xu Yong. Recent advances in evolutionary computation [J]. Journal of Computer Science and Technology, 2006, 21(1): 1–18.
Author information
Authors and Affiliations
Corresponding author
Additional information
Foundation item: Supported by the National Natural Science Foundation of China (61070008); the Humanities and Social Science Youth Fund of the Ministry of Education(11YJC870012); the Youth Fund of Jiangxi Province Department of Education (GJJ11106); the Natural Science Foundation of Colleges and Universities of Anhui Province Department of Education (KJ2010B096) and the Industrial Research Projects of Nanchang Science and Technology Bureau, Jiangxi (07110076)
Biography: WANG Zelin, male, Ph.D. candidate, research direction: evolutionary computing and network security, etc.
Rights and permissions
About this article
Cite this article
Wang, Z., Wu, Z. & Zhang, B. Packet matching algorithm based on improving differential evolution. Wuhan Univ. J. Nat. Sci. 17, 447–453 (2012). https://doi.org/10.1007/s11859-012-0868-6
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11859-012-0868-6