Analysis of Network Traffic Load Balancing Techniques in High-Load Networks
https://doi.org/10.25205/1818-7900-2025-23-3-23-31
Abstract
This article provides a comprehensive analysis of network traffic balancing methods in high-load networks. It examines fundamental load distribution principles, including requirements for maintaining TCP session integrity and specific aspects of network flow identification. The study offers a detailed investigation of modern load balancing algorithms – from classical ECMP to advanced solutions based on consistent hashing, HRW, and Maglev. Particular attention is given to the selection of optimal hash functions for network flow identification and comparative analysis of different methods’ characteristics. The presented results enable the development of recommendations for choosing balancing strategies in various operational scenarios of high-load network infrastructures.
About the Author
N. V. Krasovskaya
Novosibirsk State University
Russian Federation
Russian Federation
Nadezhda V. Krasovskaya, Master’s Student
Novosibirsk
References
1. Yasin W., Ibrahim H., Abdul Hamid N. A. W., Udzir N. I. Performance Analysis of Transport Control Protocol Flavours in the Existence of Packet Reordering Phenomena. Digital Enterprise and Information Systems, 2011, рp. 569–579. DOI: 10.1007/978-3-642-22603-8_50.
2. Olifer V. G., Olifer N. A. Computer Networks: Principles, Technologies and Protocols, 3rd Edition, Saint Petersburg, Piter publ., 2007.
3. Hopps C. Analysis of an Equal-Cost Multi-Path Algorithm. RFC Editor, Nov. 2000. DOI: 10.17487/rfc2992.
4. Larin D. V., Getman A. I. High-speed network traffic capturing and processing tools. Proceedings of the Institute for System Programming of the RAS, 2021, vol. 33, no. 4, рp. 49–68. DOI: 10.15514/ispras-2021-33(4)-4. (in Russ.)
5. Karger D., Lehman E., Leighton T., Panigrahy R., Levine M., Lewin D. Consistent hashing and random trees. Proceedings of the twenty-ninth annual ACM symposium on Theory of computing – STOC ’97, 1997, рp. 654–663. DOI: 10.1145/258533.258660.
6. Thaler D. G., Ravishankar C. V. Using name-based mappings to increase hit rates. IEEE/ACM Transactions on Networking, 1998, vol. 6, no. 1, p. 1–14. DOI: 10.1109/90.663936.
7. Eisenbud D. E., Yi C., Contavalli C., Smith C., Kononov R., Mann-Hielscher E., et al. Maglev: a fast and reliable software network load balancer. Proceedings of the 13th Usenix Conference on Networked Systems Design and Implementation (NSDI’16), 2016, Usenix Association, рp. 523–535.
8. Appleby A. Murmurhash3. Github. URL: https://github.com/aappleby/smhasher/wiki/Murmur-Hash (date of access: 17.04.2025).
9. Suparn P., Mamta R. Evaluation and Categorization of Hashing Algorithms Based on Their Applications. IAENG International Journal of Applied Mathematics, 2025, no. 55, рp. 540–552.
10. Akoto-Adjepong V., Asante M., Okyere-Gyamfi S. An Enhanced Non-Cryptographic Hash Function. International Journal of Computer Applications, 2020, vol. 176, no. 15, рp. 10–17, DOI: 10.5120/ijca2020920014.
Review
For citations:
Krasovskaya N.V. Analysis of Network Traffic Load Balancing Techniques in High-Load Networks. Vestnik NSU. Series: Information Technologies. 2025;23(3):23-31. (In Russ.) https://doi.org/10.25205/1818-7900-2025-23-3-23-31
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