Japan Photonic Network Model

Announcement of Japan Photonic Network Model Series

"Japan Photonic Network Model (JPNM)" is a model of a logical network topology model connecting prefectures in Japan. JPNM is desgined to be widely used in photonic network research, development, and business. We use publicly available regional information (station locations, railway networks, routes, distances, population, etc.), and build JPNM based on ordinary communication network design and construction methods. As a result, it has the characteristics of a network similar in structure to the actual Japanese networks owned by major telecommunications carriers, and the specific network parameters such as node locations, routes and distances are clearly indicated. In addition to JPNM created in 2013, in 2022 we newly developed and opened "Tokyo metro area network models (named TMN12 and TMN23 models)" for research in B5G/6G era.

It is expected that the JPNM series will be widely used in network research, etc., which will invigorate the research field and increase the possibility that research results will be utilized in the real world. In light of the above objectives, the JPNM Series will be made widely available to the public for research and development.

Download

Type/Detail Donwload link
Core NW model
JPN Models (JPN12, JPN25, JPN48)
JPNM_v20161013sn(E).zip(English ver.)
Metro NW model
Tokyo TMN12 Model(TMN12)& Tokyo TMN23 model(TMN23)
TokyoMANModel.zip(English ver.)

Position Paper

T. Tachibana Y. Hirota, K. Suzuki, T. Tsuritani, and H. Hasegawa, "Metropolitan Area Network Model Design using Regional Railways Information for Beyond 5G Research," IEICE Transactions on Communications, vol. E106-B, no. 4, pp. 296-306, Apr. 2023.

Examples of Utilization

[1] D. Amaya and T. Tachibana, “Heuristic-based service chain construction with security-level management,” IEICE Transactions on Communications, vol. 106, no. 12, pp.1380-1391, 2023.
[2] C. Wang, Y. Wakayama, N. Yoshikane, and T. Tsuritani, “Towards universal paradigm of QoT estimation over optical transport network through graph neural structure,” in Proc. 49th European Conference on Optical Communications (ECOC 2023), pp. 511-514, 2023.
[3] T. Kuno, T. Ochiai, R. Higuchi, K. Satake, K. Cruzado, R. Munakata, Y. Mori, S.-C. Lin, M. Matsuura, S. Subramaniam, and H. Hasegawa, “4.71-Pbps-throughput multiband OXC based on space-and wavelength-granular hybrid switching,” in Proc. International Conference on Photonics in Switching and Computing (PSC 2023), pp. 1-3, 2023.
[4] R. Nakamura, K. Urata, and S. Harada, “A heuristic spatio-temporal scheduling for virtual network allocation considering renewable energy,” in Proc. IEEE Global Communications Conference (GLOBECOM 2023), pp. 2742-2747, 2023.
[5] P. Bai, “Study on railway informatization optimization based on intelligent fusion algorithm,” in Proc. 4th International Conference on Neural Networks, Information and Communication (NNICE 2024), pp. 494-498, 2024.
[6] D. Saito, Y. Mori, K. Hosokawa, S. Yanagimachi, and H. Hasegawa, “Cost-effective capacity enhancement of survivable optical networks by supplemental band expansion and backup resource sharing,” in Proc. Optical Fiber Communications Conference and Exhibition (OFC 2024), pp. 1-3, 2024.
[7] G. Le, V. T. Hoang, S. Ferdousi, A. Marotta, S. Xu, Y. Hirota, Y. Awaji, M. Tornatore, and B. Mukherjee, “Reliable provisioning of low-latency and high-bandwidth extended reality live streams,” Authorea Preprints, 2024.
[8] N. Koneva, F. Arpanaei, A. Sánchez-Macián, and J. A. Hernández, “On designing transport networks with latency guarantees for next-generation services,” 2024.
[9] A. L. Navarro, N. Koneva, A. Sánchez-Macián, J. A. Hernández, Ó.G. de Dios, and J. M. Rivas-Moscoso, “Reinforcement-learning based routing for packet-optical networks with hybrid telemetry,” arXiv preprint, arXiv:2406.12602, 2024.
[10] A. Sánchez-Macián, N. Koneva, M. Quagliotti, J. M. Rivas-Moscoso, F. Arpanaei, J. A. Hernández, J. P. Fernández-Palacios, L. Zhang, and E. Riccardi, “MoleNetwork: A tool for the generation of synthetic optical network topologies,” arXiv preprint, arXiv:2408.01721, 2024.
[11] K. Higashimori, T. Tanaka, and T. Inoue, “Routing problem for reducing significant outages in optical networks and its system analysis,” Optica Journal of Optical Communications and Networking, vol. 16, no. 9, pp. E1-E10, 2024.