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Effects of Traffic Direction and IP Type on Dual-Stack Routing Performance in 5G Mesh Networks
Corresponding Author(s) : Fadli Sirait
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control,
Vol. 11, No. 4, November 2026 (Article in Progress)
Abstract
The coexistence of Internet Protocol version 4 (IPv4) and Internet Protocol version 6 (IPv6) remains important in next-generation communication networks. This study examined the joint effects of traffic direction and IP version on routing performance in a GNS3-based dual-stack mesh emulation designed as a 5G-oriented network-layer abstraction. The model represents multi-hop IPv4/IPv6 routing over high-capacity links and does not emulate the 5G radio access network or 5G Core. A balanced factorial experiment was designed by combining two bandwidth levels, two file sizes, three routing protocols, two traffic directions, and two IP versions. Each of the 48 experimental conditions was scheduled for six repetitions, yielding 288 planned run records. After data verification, 285 valid observations were included in the primary analysis. Throughput, transfer time, end-to-end delay, and packet loss ratio were analyzed using ordinary least-squares factorial models with HC3 robust covariance. Traffic direction significantly affected all four-performance metrics. Download traffic produced higher throughput, shorter transfer time, lower delay, and lower packet loss ratio than upload traffic under both IP versions. IP version significantly affected throughput and transfer time but did not produce significant overall effects on delay or packet loss ratio. Significant Direction × IP Version interactions were observed for throughput, delay, and packet loss ratio, indicating that IPv4–IPv6 performance differences depended on traffic direction. Routing protocol was not statistically significant for any metric; therefore, protocol-level differences were interpreted descriptively rather than as confirmed rankings. These findings demonstrate that dual-stack routing performance is direction-dependent and should be evaluated using traffic-aware factorial analysis rather than separate or aggregated IPv4–IPv6 comparisons.
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References
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R. Goyal, “Characterizing Ipv6 Adoption Trends Through Longitudinal Measurements,” JISIS, vol. 15, no. 4, pp. 62–75, Nov. 2025, doi: 10.58346/JISIS.2025.I4.005.
A. Hamarsheh et al., “Comparative Evaluation of Host-Based Translator Mechanisms for IPv4-IPv6 Communication Performance Analysis With Different Routing Protocols:,” International Journal of Cloud Applications and Computing, vol. 13, no. 1, pp. 1–26, Oct. 2023, doi: 10.4018/IJCAC.332765.
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T. Zhuang, Z. Shu, S. Chen, Q. Tu, H. Xie, and Z. Xu, “Intelligent algorithm for dynamic handling of DDoS based on action cost in a dual-Stack environment,” Computer Networks, vol. 278, p. 112105, Apr. 2026, doi: 10.1016/j.comnet.2026.112105.
M. Hu, L. Zhang, Y. Guo, L. Cheng, W. Du, and X. Ma, “Hostname Correlation Based IPv6 Address Fast Scanning Technology of Windows Nodes,” in 2022 IEEE 22nd International Conference on Communication Technology (ICCT), Nanjing, China: IEEE, Nov. 2022, pp. 1353–1357. doi: 10.1109/ICCT56141.2022.10073249.
F. Osali, K. Z. Sediqi, and O. Gasser, “Sibling Prefixes: Identifying Similarities in IPv4 and IPv6 Prefixes,” in Proceedings of the 2025 ACM Internet Measurement Conference, Madison WI USA: ACM, Oct. 2025, pp. 100–119. doi: 10.1145/3730567.3732917.
X. Wang, Z. Li, and Q. Wang, “Research on Dynamic Plugin Scheduling and Intelligent Switching of IPv4/IPv6 Protocol Stacks Based on Reinforcement Learning,” in 2025 10th International Conference on Cyber Security and Information Engineering (ICCSIE), Xining, China: IEEE, Jul. 2025, pp. 556–560. doi: 10.1109/ICCSIE65832.2025.00102.
S. Li, Y. Yi, and K. Zhu, “Implementation and scheme of IPv4 to IPv6 Transition in enterprise network architecture,” in 2021 IEEE 2nd International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA), Chongqing, China: IEEE, Dec. 2021, pp. 457–461. doi: 10.1109/ICIBA52610.2021.9688000.
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