{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T21:15:26Z","timestamp":1792790126177,"version":"4.5.0"},"reference-count":54,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2025,2,18]],"date-time":"2025-02-18T00:00:00Z","timestamp":1739836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2020YFB1808004"],"award-info":[{"award-number":["2020YFB1808004"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["BE2021013-2"],"award-info":[{"award-number":["BE2021013-2"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Jiangsu Key Research and Development Program","award":["2020YFB1808004"],"award-info":[{"award-number":["2020YFB1808004"]}]},{"name":"Jiangsu Key Research and Development Program","award":["BE2021013-2"],"award-info":[{"award-number":["BE2021013-2"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Low-orbit satellite communication networks have gradually become the research focus of fifth-generation (5G) beyond and sixth generation (6G) networks due to their advantages of wide coverage, large communication capacity, and low terrain influence. However, the low earth orbit mega satellite network (LEO-MSN) also has difficulty in constructing stable traffic transmission paths, network load imbalance and congestion due to the large scale of network nodes, a highly complex topology, and uneven distribution of traffic flow in time and space. In the service-based architecture proposed by 3GPP, the introduction of service function chain (SFC) constraints exacerbates these challenges. Therefore, in this paper, we propose GDRL-SFCR, an end-to-end routing decision method based on graph neural network (GNN) and deep reinforcement learning (DRL) which jointly optimize the end-to-end transmission delay and network load balancing under SFC constraints. Specifically, this method constructs the system model based on the latest NTN low-orbit satellite network end-to-end transmission architecture, taking into account the SFC constraints, transmission delays, and network node loads in the end-to-end traffic transmission, uses a GNN to extract node attributes and dynamic topology features, and uses the DRL method to design specific reward functions to train the model to learn routing policies that satisfy the SFC constraints. The simulation results demonstrate that, compared with graph theory-based methods and reinforcement learning-based methods, GDRL-SFCR can reduce the end-to-end traffic transmission delay by more than 11.3%, reduce the average network load by more than 14.1%, and increase the traffic access success rate and network capacity by more than 19.1% and two times, respectively.<\/jats:p>","DOI":"10.3390\/s25041232","type":"journal-article","created":{"date-parts":[[2025,2,18]],"date-time":"2025-02-18T03:47:06Z","timestamp":1739850426000},"page":"1232","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Deep Reinforcement Learning-Based Routing Method for Low Earth Orbit Mega-Constellation Satellite Networks with Service Function Constraints"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-1233-3357","authenticated-orcid":false,"given":"Yan","family":"Chen","sequence":"first","affiliation":[{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"State Key Laboratory of Processors, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huan","family":"Cao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Processors, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Longhe","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Processors, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daojin","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Processors, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-9215-7956","authenticated-orcid":false,"given":"Zifan","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Processors, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiqing","family":"Zhou","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"State Key Laboratory of Processors, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing 100190, China"},{"name":"Nanjing Mobile Communication and Computing Innovation Institute, Chinese Academy of Sciences, Nanjing 211135, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinglin","family":"Shi","sequence":"additional","affiliation":[{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"State Key Laboratory of Processors, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing 100190, China"},{"name":"Nanjing Mobile Communication and Computing Innovation Institute, Chinese Academy of Sciences, Nanjing 211135, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,2,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2317","DOI":"10.1109\/TCOMM.2023.3241328","article-title":"Hardware-impaired RIS-assisted mmWave hybrid systems: Beamforming design and performance analysis","volume":"71","author":"Gong","year":"2023","journal-title":"IEEE Trans. Commun."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1827","DOI":"10.1109\/TCOMM.2023.3239932","article-title":"Transmissive metasurfaces assisted wireless communications on railways: Channel strength evaluation and performance analysis","volume":"71","author":"Lin","year":"2023","journal-title":"IEEE Trans. Commun."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/j.dcan.2020.05.003","article-title":"Service-aware 6G: An intelligent and open network based on the convergence of communication, computing and caching","volume":"6","author":"Zhou","year":"2020","journal-title":"Digit. Commun. Netw."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1109\/JSAC.2023.3234696","article-title":"Improved grant-free access for URLLC via multi-tier-driven computing: Network-load learning, prediction, and resource allocation","volume":"41","author":"Zhao","year":"2023","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1584","DOI":"10.1109\/JSAC.2019.2916280","article-title":"Economically optimal MS association for multimedia content delivery in cache-enabled heterogeneous cloud radio access networks","volume":"37","author":"Liu","year":"2019","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1109\/COMST.2023.3249835","article-title":"On the road to 6G: Visions, requirements, key technologies, and testbeds","volume":"25","author":"Wang","year":"2023","journal-title":"IEEE Commun. Surv. Tutorials"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"100986","DOI":"10.1109\/ACCESS.2023.3314732","article-title":"Empowering non-terrestrial networks with artificial intelligence: A survey","volume":"11","author":"Iqbal","year":"2023","journal-title":"IEEE Access"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1109\/MNET.2024.3352130","article-title":"Architecture, Characteristics, and Resource Management of Integration of Sensing, Communications, and Computing in 6G","volume":"38","author":"Qi","year":"2024","journal-title":"IEEE Netw."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"013","DOI":"10.53430\/ijeru.2024.6.2.0024","article-title":"A comprehensive review of energy-efficient design in satellite communication systems","volume":"6","author":"Esho","year":"2024","journal-title":"Int. J. Eng. Res. Updat."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1109\/MCOM.002.2200018","article-title":"Space-air-ground FSO networks for high-throughput satellite communications","volume":"60","author":"Samy","year":"2022","journal-title":"IEEE Commun. Mag."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1109\/MWC.2019.1800299","article-title":"Broadband LEO satellite communications: Architectures and key technologies","volume":"26","author":"Su","year":"2019","journal-title":"IEEE Wirel. Commun."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"35040","DOI":"10.1109\/ACCESS.2022.3162243","article-title":"LEO satellites in 5G and beyond networks: A review from a standardization perspective","volume":"10","author":"Darwish","year":"2022","journal-title":"IEEE Access"},{"key":"ref_13","first-page":"281","article-title":"The itu imt-2020 standardization: Lessons from 5g and future perspectives for 6g","volume":"12","author":"Whalley","year":"2022","journal-title":"J. Inf. Policy"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.aej.2022.08.017","article-title":"6G mobile communication technology: Requirements, targets, applications, challenges, advantages, and opportunities","volume":"64","author":"Banafaa","year":"2023","journal-title":"Alex. Eng. J."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1279","DOI":"10.1109\/COMST.2023.3347145","article-title":"Revolutionizing future connectivity: A contemporary survey on AI-empowered satellite-based non-terrestrial networks in 6G","volume":"26","author":"Mahboob","year":"2024","journal-title":"IEEE Commun. Surv. Tutorials"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Mohanta, K., and Al-Rubaye, S. (2024). Towards 6G Satellite\u2013Terrestrial Networks: Analysis of Air Mobility Operations. Electronics, 13.","DOI":"10.3390\/electronics13142855"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"64","DOI":"10.23919\/JCC.2022.01.006","article-title":"6G service coverage with mega satellite constellations","volume":"19","author":"Sheng","year":"2022","journal-title":"China Commun."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1109\/MWC.011.2200310","article-title":"LEO satellite access network (LEO-SAN) towards 6G: Challenges and approaches","volume":"31","author":"Xiao","year":"2022","journal-title":"IEEE Wirel. Commun."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Glenn, A.B., Collen, P.L., and McGilvray, M. (2022, January 3\u20137). Experimental Non-Equilibrium Radiation Measurements for Low-Earth Orbit Return. Proceedings of the AIAA SciTech 2022 Forum, San Diego, CA, USA.","DOI":"10.2514\/6.2022-2154"},{"key":"ref_20","unstructured":"(2024, November 20). NORAD GP Element Sets Current Data. Available online: https:\/\/celestrak.com\/NORAD\/elements\/."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"30","DOI":"10.22495\/cbsrv5i1art3","article-title":"The Spacex Starlink Satellite Project: Business Strategies and Perspectives","volume":"5","author":"Shaengchart","year":"2024","journal-title":"Corp. Bus. Strategy Rev."},{"key":"ref_22","first-page":"383","article-title":"The Status Quo and Prospect of Satellite Network Routing Technology","volume":"45","author":"Ni","year":"2023","journal-title":"J. Electron. Inf. Technol."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Cao, X., Li, Y., Xiong, X., and Wang, J. (2022). Dynamic routings in satellite networks: An overview. Sensors, 22.","DOI":"10.3390\/s22124552"},{"key":"ref_24","unstructured":"3GPP (2024, November 20). Study on New Radio (NR) to Support Non-Terrestrial Networks. Technical Report (TR) 38.811, 3rd Generation Partnership Project (3GPP). Available online: https:\/\/portal.3gpp.org\/desktopmodules\/Specifications\/SpecificationDetails.aspx?specificationId=3234."},{"key":"ref_25","unstructured":"3GPP (2024, November 20). Solutions for NR to Support Non-Terrestrial Networks (NTN). Technical Report (TR) 38.821, 3rd Generation Partnership Project (3GPP). Available online: https:\/\/portal.3gpp.org\/desktopmodules\/Specifications\/SpecificationDetails.aspx?specificationId=3525."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2909","DOI":"10.1109\/TWC.2021.3116983","article-title":"Maximum flow routing strategy for space information network with service function constraints","volume":"21","author":"Yang","year":"2021","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1109\/LWC.2018.2872996","article-title":"Time-expanded graph-based resource allocation over the satellite networks","volume":"8","author":"Wang","year":"2018","journal-title":"IEEE Wirel. Commun. Lett."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"102884","DOI":"10.1016\/j.jnca.2020.102884","article-title":"Routing in the space internet: A contact graph routing tutorial","volume":"174","author":"Fraire","year":"2021","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.adhoc.2017.01.006","article-title":"A maximum flow algorithm based on storage time aggregated graph for delay-tolerant networks","volume":"59","author":"Li","year":"2017","journal-title":"Ad Hoc Netw."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"6912","DOI":"10.1109\/TCOMM.2019.2929757","article-title":"STAG-based QoS support routing strategy for multiple missions over the satellite networks","volume":"67","author":"Zhang","year":"2019","journal-title":"IEEE Trans. Commun."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Wu, Z., Hu, G., Jin, F., Jiang, B., and Fu, Y. (2015, January 15\u201317). Agent-based dynamic routing in the packet-switched LEO satellite networks. Proceedings of the 2015 International Conference on Wireless Communications & Signal Processing (WCSP), Nanjing, China.","DOI":"10.1109\/WCSP.2015.7341005"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"112044","DOI":"10.1109\/ACCESS.2019.2934932","article-title":"Load-balancing routing algorithm based on segment routing for traffic return in LEO satellite networks","volume":"7","author":"Liu","year":"2019","journal-title":"IEEE Access"},{"key":"ref_33","first-page":"25","article-title":"Joint multi-QoS and energy saving routing for LEO satellite network","volume":"26","author":"Yang","year":"2019","journal-title":"J. China Univ. Posts Telecommun."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Xu, M., Jia, M., and Guo, Q. (2023, January 20\u201322). Delay-Sensitive SFC Scheduling Optimization with DRL in Satellite-Terrestrial Networks. Proceedings of the 2023 IEEE 23rd International Conference on Communication Technology (ICCT), Wuxi, China.","DOI":"10.1109\/ICCT59356.2023.10419739"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1109\/TMC.2022.3225239","article-title":"Computing and communication cost-aware service migration enabled by transfer reinforcement learning for dynamic vehicular edge computing networks","volume":"23","author":"Peng","year":"2022","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"9640","DOI":"10.1109\/TWC.2023.3272920","article-title":"How to tame mobility in federated learning over mobile networks?","volume":"22","author":"Peng","year":"2023","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Zha, P., Long, C., Wu, J., and Li, S. (2020, January 6\u20138). Satellite lifetime predicted greedy perimeter stateless routing protocol for LEO satellite network. Proceedings of the 2020 Chinese Automation Congress (CAC), Shanghai, China.","DOI":"10.1109\/CAC51589.2020.9326774"},{"key":"ref_38","unstructured":"Yi, Z., Quan, Z., Jun, L., and Wei, L. (2015, January 16\u201318). The generation and update algorithm of routing table in satellite network. Proceedings of the 2015 IEEE International Conference on Communication Problem-Solving (ICCP), Guilin, China."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Zuo, P., Wang, C., Wei, Z., Li, Z., Zhao, H., and Jiang, H. (2022, January 19\u201322). Deep reinforcement learning based load balancing routing for LEO satellite network. Proceedings of the 2022 IEEE 95th Vehicular Technology Conference:(VTC2022-Spring), Helsinki, Finland.","DOI":"10.1109\/VTC2022-Spring54318.2022.9860582"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.chinastron.2009.12.009","article-title":"An accuracy analysis of the SGP4\/SDP4 model","volume":"34","author":"Dong","year":"2010","journal-title":"Chin. Astron. Astrophys."},{"key":"ref_41","unstructured":"Anttonen, A., Ruuska, P., and Kiviranta, M. (2019). 3GPP Nonterrestrial Networks: A Concise Review and Look Ahead, VTT Technical Research Centre of Finland."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1109\/MAES.2021.3072690","article-title":"Review of 5G NTN standards development and technical challenges for satellite integration with the 5G network","volume":"36","author":"Hosseinian","year":"2021","journal-title":"IEEE Aerosp. Electron. Syst. Mag."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1230","DOI":"10.1109\/TNET.2021.3137418","article-title":"A robustness-aware real-time SFC routing update scheme in multi-tenant clouds","volume":"30","author":"Tu","year":"2022","journal-title":"IEEE\/ACM Trans. Netw."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1561\/2200000071","article-title":"An introduction to deep reinforcement learning","volume":"11","author":"Henderson","year":"2018","journal-title":"Found. Trends. Mach. Learn."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"7189","DOI":"10.1109\/JIOT.2022.3229028","article-title":"Age-optimized multihop information update mechanism on the LEO satellite constellation via continuous time-varying graphs","volume":"10","author":"Li","year":"2022","journal-title":"IEEE Internet Things J."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"3925","DOI":"10.1109\/TNNLS.2021.3120100","article-title":"Gpens: Graph data learning with graph propagation-embedding networks","volume":"34","author":"Jiang","year":"2021","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_47","unstructured":"Chen, M., Wei, Z., Huang, Z., Ding, B., and Li, Y. (2020, January 13\u201318). Simple and deep graph convolutional networks. Proceedings of the International Conference on Machine Learning, PMLR, Online."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.comcom.2021.12.015","article-title":"Graph-based deep learning for communication networks: A survey","volume":"185","author":"Jiang","year":"2022","journal-title":"Comput. Commun."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"5330","DOI":"10.1109\/TWC.2023.3325735","article-title":"ENGNN: A general edge-update empowered GNN architecture for radio resource management in wireless networks","volume":"23","author":"Wang","year":"2023","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_50","unstructured":"Schulman, J., Wolski, F., Dhariwal, P., Radford, A., and Klimov, O. (2017). Proximal policy optimization algorithms. arXiv."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"2743","DOI":"10.1109\/TVT.2021.3058126","article-title":"Analysis of inter-satellite link paths for LEO mega-constellation networks","volume":"70","author":"Chen","year":"2021","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Cakaj, S. (2021). The parameters comparison of the \u201cStarlink\u201d LEO satellites constellation for different orbital shells. Front. Commun. Netw., 2.","DOI":"10.3389\/frcmn.2021.643095"},{"key":"ref_53","unstructured":"Warszawski, L., Frieler, K., Huber, V., Piontek, F., Serdeczny, O., Zhang, X., Tang, Q., Pan, M., Tang, Y., and Tang, Q. (2017). Center for international earth science information network\u2014Ciesin\u2014Columbia university. (2016). gridded population of the world, version 4 (gpwv4): Population density. palisades. ny: Nasa socioeconomic data and applications center (sedac). Atlas of Environmental Risks Facing China Under Climate Change, Springer."},{"key":"ref_54","unstructured":"Huang, S., Chen, W., Sun, Y., Bie, F., and Tu, W.W. (2023). OpenRL: A Unified Reinforcement Learning Framework. arXiv."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/25\/4\/1232\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T16:36:42Z","timestamp":1760027802000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/25\/4\/1232"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,18]]},"references-count":54,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2025,2]]}},"alternative-id":["s25041232"],"URL":"https:\/\/doi.org\/10.3390\/s25041232","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,18]]}}}