{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T11:49:55Z","timestamp":1783511395586,"version":"3.55.0"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,12,20]],"date-time":"2024-12-20T00:00:00Z","timestamp":1734652800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,20]],"date-time":"2024-12-20T00:00:00Z","timestamp":1734652800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100013099","name":"Scientific Research Fund of Liaoning Provincial Education Department","doi-asserted-by":"publisher","award":["202414226-1"],"award-info":[{"award-number":["202414226-1"]}],"id":[{"id":"10.13039\/501100013099","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Netw Syst Manage"],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1007\/s10922-024-09895-9","type":"journal-article","created":{"date-parts":[[2024,12,20]],"date-time":"2024-12-20T18:48:58Z","timestamp":1734720538000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Adaptive UE Handover Management with MAR-Aided Multivariate DQN in Ultra-Dense Networks"],"prefix":"10.1007","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-9833-4231","authenticated-orcid":false,"given":"Weiran","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0417-6313","authenticated-orcid":false,"given":"Heng","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8563-7198","authenticated-orcid":false,"given":"Shanshan","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8113-0112","authenticated-orcid":false,"given":"Xue","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-3046-2641","authenticated-orcid":false,"given":"Zhaojun","family":"Wan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,12,20]]},"reference":[{"key":"9895_CR1","doi-asserted-by":"publisher","first-page":"12803","DOI":"10.1109\/ACCESS.2021.3051097","volume":"9","author":"J Angjo","year":"2021","unstructured":"Angjo, J., Shayea, I., Ergen, M., et al.: Handover management of drones in future mobile networks: 6g technologies. IEEE Access 9, 12803\u201312823 (2021). https:\/\/doi.org\/10.1109\/ACCESS.2021.3051097","journal-title":"IEEE Access"},{"issue":"16","key":"9895_CR2","doi-asserted-by":"publisher","first-page":"12855","DOI":"10.1109\/JIOT.2021.3068463","volume":"8","author":"D Zhao","year":"2021","unstructured":"Zhao, D., Yan, Z., Wang, M., et al.: Is 5G handover secure and private? a survey. IEEE Internet Things J. 8(16), 12855\u201312879 (2021). https:\/\/doi.org\/10.1109\/JIOT.2021.3068463","journal-title":"IEEE Internet Things J."},{"key":"9895_CR3","doi-asserted-by":"crossref","unstructured":"da Silva, Brilhante D., de Rezende, J.F., Marchetti, N.: Handover optimisation for high-capacity low-latency 5G NR mmWave communication. Ad Hoc Net. (2024)","DOI":"10.2139\/ssrn.4510848"},{"issue":"4","key":"9895_CR4","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1007\/s10922-024-09858-0","volume":"32","author":"A Bennaoui","year":"2024","unstructured":"Bennaoui, A., Guezouri, M., Keche, M.: Improving VANET data dissemination efficiency with deep neural networks. J. Netw. Syst. Manag. 32(4), 81 (2024). https:\/\/doi.org\/10.1007\/s10922-024-09858-0","journal-title":"J. Netw. Syst. Manag."},{"issue":"1","key":"9895_CR5","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1007\/s10922-022-09713-0","volume":"31","author":"H Hu","year":"2023","unstructured":"Hu, H., Zhang, W., Xu, L., et al.: A mobility-aware service function chain migration strategy based on deep reinforcement learning. J. Netw. Syst. Manag. 31(1), 21 (2023). https:\/\/doi.org\/10.1007\/s10922-022-09713-0","journal-title":"J. Netw. Syst. Manag."},{"issue":"2","key":"9895_CR6","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1007\/s10922-024-09804-0","volume":"32","author":"H Hassen","year":"2024","unstructured":"Hassen, H., Meherzi, S., Jemaa, Z.B.: Improved exploration strategy for Q-learning based multipath routing in SDN networks. J. Netw. Syst. Manag. 32(2), 25 (2024). https:\/\/doi.org\/10.1007\/s10922-024-09804-0","journal-title":"J. Netw. Syst. Manag."},{"key":"9895_CR7","doi-asserted-by":"publisher","unstructured":"Wang Y, Xiao Y, Song Y, et\u00a0al (2023) Deep Reinforcement Learning Based Probabilistic Cognitive Routing: An Empirical Study with OMNeT++ and P4. In: 2023 19th International Conference on Network and Service Management (CNSM), IEEE, pp 1\u20137, https:\/\/doi.org\/10.23919\/CNSM59352.2023.10327868","DOI":"10.23919\/CNSM59352.2023.10327868"},{"key":"9895_CR8","doi-asserted-by":"publisher","unstructured":"Mudvari, A., Tassiulas, L.: Joint SDN Synchronization and Controller Placement in Wireless Networks using Deep Reinforcement Learning. In: NOMS 2024-2024 IEEE Network Operations and Management Symposium, IEEE, pp. 1\u20139 (2024). https:\/\/doi.org\/10.1109\/NOMS59830.2024.10575746","DOI":"10.1109\/NOMS59830.2024.10575746"},{"key":"9895_CR9","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2024.3352014","author":"AA Okine","year":"2024","unstructured":"Okine, A.A., Adam, N., Naeem, F., et al.: Multi-agent deep reinforcement learning for packet routing in tactical mobile sensor networks. IEEE Trans. Netw. Serv. Manag. (2024). https:\/\/doi.org\/10.1109\/TNSM.2024.3352014","journal-title":"IEEE Trans. Netw. Serv. Manag."},{"issue":"2","key":"9895_CR10","doi-asserted-by":"publisher","first-page":"e2252","DOI":"10.1002\/nem.2252","volume":"34","author":"K Arakawa","year":"2024","unstructured":"Arakawa, K., Oki, E.: Availability-aware virtual network function placement based on multidimensional universal generating functions. Int. J. Netw. Manag. 34(2), e2252 (2024)","journal-title":"Int. J. Netw. Manag."},{"key":"9895_CR11","doi-asserted-by":"publisher","unstructured":"Aboud, A., Touati, H., Hnich, B.: Markov Chain based Predictive Model for Efficient handover Management in Vehicle-to-Infrastructure Communications. In: 2021 International Wireless Communications and Mobile Computing (IWCMC), IEEE, pp. 1117\u20131122 (2021). https:\/\/doi.org\/10.1109\/IWCMC51323.2021.9498927","DOI":"10.1109\/IWCMC51323.2021.9498927"},{"issue":"1","key":"9895_CR12","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1109\/MVT.2019.2959065","volume":"15","author":"C Lee","year":"2020","unstructured":"Lee, C., Cho, H., Song, S., et al.: Prediction-based conditional handover for 5G mm-wave networks: a deep-learning approach. IEEE Veh. Technol. Mag. 15(1), 54\u201362 (2020). https:\/\/doi.org\/10.1109\/MVT.2019.2959065","journal-title":"IEEE Veh. Technol. Mag."},{"key":"9895_CR13","unstructured":"Masri, A., Veijalainen, T., Martikainen, H. et\u00a0al.: Machine-Learning-Based Predictive Handover. In: 2021 IFIP\/IEEE International Symposium on Integrated Network Management (IM), IEEE, pp. 648\u2013652 (2021)"},{"issue":"1","key":"9895_CR14","doi-asserted-by":"publisher","first-page":"e4907","DOI":"10.1002\/ett.4907","volume":"35","author":"H Wang","year":"2024","unstructured":"Wang, H., Li, B.: Double-deep Q-learning-based handover management in mmWave heterogeneous networks with dual connectivity. Trans. Emerg. Telecommun. Technol. 35(1), e4907 (2024)","journal-title":"Trans. Emerg. Telecommun. Technol."},{"key":"9895_CR15","doi-asserted-by":"publisher","unstructured":"Prado, A., Vijayaraghavan, H., Kellerer, W.: ECHO: Enhanced Conditional Handover boosted by Trajectory Prediction. In: 2021 IEEE Global Communications Conference (GLOBECOM), IEEE, pp. 01\u201306 (2021). https:\/\/doi.org\/10.1109\/GLOBECOM46510.2021.9685348","DOI":"10.1109\/GLOBECOM46510.2021.9685348"},{"key":"9895_CR16","doi-asserted-by":"publisher","first-page":"122871","DOI":"10.1016\/j.eswa.2023.122871","volume":"246","author":"CF Kwong","year":"2024","unstructured":"Kwong, C.F., Shi, C., Liu, Q., Yang, S., Chieng, D., Kar, P.: Autonomous handover parameter optimisation for 5G cellular networks using deep deterministic policy gradient. Expert Syst. Appl. 246, 122871 (2024)","journal-title":"Expert Syst. Appl."},{"key":"9895_CR17","doi-asserted-by":"publisher","DOI":"10.1109\/TMLCN.2023.3319286","author":"S Ohta","year":"2023","unstructured":"Ohta, S., Nishio, T., Kudo, R., et al.: Point cloud-based proactive link quality prediction for millimeter-wave communications. IEEE Trans. Mach. Learn. Commun. Netw. (2023). https:\/\/doi.org\/10.1109\/TMLCN.2023.3319286","journal-title":"IEEE Trans. Mach. Learn. Commun. Netw."},{"key":"9895_CR18","doi-asserted-by":"publisher","unstructured":"Stanczak, J., Karabulut, U., Awada, A.: Conditional Handover in 5G - Principles, Future Use Cases and FR2 Performance. In: 2022 International Wireless Communications and Mobile Computing (IWCMC), IEEE, pp. 660\u2013665, (2022). https:\/\/doi.org\/10.1109\/IWCMC55113.2022.9824571","DOI":"10.1109\/IWCMC55113.2022.9824571"},{"key":"9895_CR19","doi-asserted-by":"publisher","unstructured":"Iqbal, S.B., Awada, A., Karabulut, U. et\u00a0al.: On the Modeling and Analysis of Fast Conditional Handover for 5G-Advanced. In: 2022 IEEE 33rd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), IEEE, pp. 595\u2013601 (2022). https:\/\/doi.org\/10.1109\/PIMRC54779.2022.9977719","DOI":"10.1109\/PIMRC54779.2022.9977719"},{"key":"9895_CR20","doi-asserted-by":"publisher","first-page":"30040","DOI":"10.1109\/ACCESS.2023.3260630","volume":"11","author":"SB Iqbal","year":"2023","unstructured":"Iqbal, S.B., Nadaf, S., Awada, A., et al.: On the analysis and optimization of fast conditional handover with hand blockage for mobility. IEEE Access 11, 30040\u201330056 (2023). https:\/\/doi.org\/10.1109\/ACCESS.2023.3260630","journal-title":"IEEE Access"},{"key":"9895_CR21","doi-asserted-by":"publisher","first-page":"24446","DOI":"10.1109\/ACCESS.2021.3056945","volume":"9","author":"M Tayyab","year":"2021","unstructured":"Tayyab, M., Koudouridis, G.P., Gelabert, X., et al.: Uplink reference signals for power-efficient handover in cellular networks with mobile relays. IEEE Access 9, 24446\u201324461 (2021). https:\/\/doi.org\/10.1109\/ACCESS.2021.3056945","journal-title":"IEEE Access"},{"issue":"6","key":"9895_CR22","doi-asserted-by":"publisher","first-page":"1833","DOI":"10.1109\/JSAC.2021.3071852","volume":"39","author":"MF \u00d6zko\u00e7","year":"2021","unstructured":"\u00d6zko\u00e7, M.F., Koutsaftis, A., Kumar, R., et al.: The impact of multi-connectivity and handover constraints on millimeter wave and terahertz cellular networks. IEEE J. Sel. Areas Commun. 39(6), 1833\u20131853 (2021). https:\/\/doi.org\/10.1109\/JSAC.2021.3071852","journal-title":"IEEE J. Sel. Areas Commun."},{"issue":"3","key":"9895_CR23","doi-asserted-by":"publisher","first-page":"746","DOI":"10.3390\/s22030746","volume":"22","author":"M Chiputa","year":"2022","unstructured":"Chiputa, M., Zhang, M., Ali, G.M.N., et al.: Enhancing handover for 5G mmWave mobile networks using jump markov linear system and deep reinforcement learning. Sensors 22(3), 746 (2022). https:\/\/doi.org\/10.3390\/s22030746","journal-title":"Sensors"},{"issue":"1","key":"9895_CR24","doi-asserted-by":"publisher","first-page":"498","DOI":"10.1109\/TNSM.2021.3050627","volume":"18","author":"H Tong","year":"2021","unstructured":"Tong, H., Wang, T., Zhu, Y., et al.: Mobility-aware seamless handover With MPTCP in software-defined HetNets. IEEE Trans. Netw. Serv. Manag. 18(1), 498\u2013510 (2021). https:\/\/doi.org\/10.1109\/TNSM.2021.3050627","journal-title":"IEEE Trans. Netw. Serv. Manag."},{"key":"9895_CR25","doi-asserted-by":"publisher","first-page":"117910","DOI":"10.1109\/ACCESS.2021.3107325","volume":"9","author":"RT Rodoshi","year":"2021","unstructured":"Rodoshi, R.T., Kim, T., Choi, W.: Fuzzy logic and accelerated reinforcement learning-based user association for dense C-RANs. IEEE Access 9, 117910\u2013117924 (2021). https:\/\/doi.org\/10.1109\/ACCESS.2021.3107325","journal-title":"IEEE Access"},{"key":"9895_CR26","doi-asserted-by":"publisher","first-page":"64224","DOI":"10.1109\/ACCESS.2021.3075324","volume":"9","author":"IA Alablani","year":"2021","unstructured":"Alablani, I.A., Arafah, M.A.: An adaptive cell selection scheme for 5G heterogeneous ultra-dense networks. IEEE Access 9, 64224\u201364240 (2021). https:\/\/doi.org\/10.1109\/ACCESS.2021.3075324","journal-title":"IEEE Access"},{"key":"9895_CR27","doi-asserted-by":"publisher","first-page":"103204","DOI":"10.1016\/j.jnca.2021.103204","volume":"193","author":"X Yan","year":"2021","unstructured":"Yan, X., Ma, M.: A lightweight and secure handover authentication scheme for 5G network using neighbour base stations. J. Netw. Comput. Appl. 193, 103204 (2021)","journal-title":"J. Netw. Comput. Appl."},{"key":"9895_CR28","doi-asserted-by":"publisher","unstructured":"Yan, X., Ma, M.: NSEHA: A Neighbor-based Secure and Efficient Handover Authentication Mechanism for 5G Networks. In: Proceedings of the 2021 9th International Conference on Communications and Broadband Networking, pp. 209\u2013216 (2021). https:\/\/doi.org\/10.1145\/3456415.3456449","DOI":"10.1145\/3456415.3456449"},{"key":"9895_CR29","doi-asserted-by":"publisher","unstructured":"Oulaaffart, M., Badonnel, R., Bianco, C.: An Automated SMT-based Security Framework for Supporting Migrations in Cloud Composite Services. In: NOMS 2022-2022 IEEE\/IFIP Network Operations and Management Symposium, IEEE, pp. 1\u20139 (2022). https:\/\/doi.org\/10.1109\/NOMS54207.2022.9789768","DOI":"10.1109\/NOMS54207.2022.9789768"},{"key":"9895_CR30","doi-asserted-by":"publisher","first-page":"42529","DOI":"10.1109\/ACCESS.2022.3168843","volume":"10","author":"D Kwon","year":"2022","unstructured":"Kwon, D., Son, S., Park, Y., et al.: Design of secure handover authentication scheme for urban air mobility environments. IEEE Access 10, 42529\u201342541 (2022). https:\/\/doi.org\/10.1109\/ACCESS.2022.3168843","journal-title":"IEEE Access"},{"key":"9895_CR31","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1186\/s13638-023-02261-4","volume":"1","author":"A Haghrah","year":"2023","unstructured":"Haghrah, A., Abdollahi, M.P., Azarhava, H., et al.: (2023) A survey on the handover management in 5G-NR cellular networks: aspects, approaches and challenges. EURASIP J. Wirel. Commun. Netw. 1, 52 (2023). https:\/\/doi.org\/10.1186\/s13638-023-02261-4","journal-title":"EURASIP J. Wirel. Commun. Netw."},{"key":"9895_CR32","doi-asserted-by":"publisher","first-page":"45770","DOI":"10.1109\/ACCESS.2021.3067503","volume":"9","author":"MS Mollel","year":"2021","unstructured":"Mollel, M.S., Abubakar, A.I., Ozturk, M., et al.: A survey of machine learning applications to handover management in 5G and beyond. IEEE Access 9, 45770\u201345802 (2021). https:\/\/doi.org\/10.1109\/ACCESS.2021.3067503","journal-title":"IEEE Access"},{"issue":"1","key":"9895_CR33","doi-asserted-by":"publisher","first-page":"426","DOI":"10.3390\/app12010426","volume":"12","author":"J Tanveer","year":"2022","unstructured":"Tanveer, J., Haider, A., Ali, R., et al.: An overview of reinforcement learning algorithms for handover management in 5G ultra-dense small cell networks. Appl. Sci. 12(1), 426 (2022). https:\/\/doi.org\/10.3390\/app12010426","journal-title":"Appl. Sci."},{"key":"9895_CR34","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1007\/s11036-020-01718-w","volume":"26","author":"Q Liu","year":"2021","unstructured":"Liu, Q., Kwong, C.F., Wei, S., et al.: Intelligent handover triggering mechanism in 5G ultra-dense networks via clustering-based reinforcement learning. Mobile Netw. Appl. 26, 27\u201339 (2021). https:\/\/doi.org\/10.1007\/s11036-020-01718-w","journal-title":"Mobile Netw. Appl."},{"key":"9895_CR35","doi-asserted-by":"publisher","unstructured":"Koda, Y., Yamamoto, K., Nishio, T. et\u00a0al.: Reinforcement learning based predictive handover for pedestrian-aware mmWave networks. In: IEEE INFOCOM 2018-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), IEEE, pp. 692\u2013697 (2018) https:\/\/doi.org\/10.1109\/INFCOMW.2018.8406993","DOI":"10.1109\/INFCOMW.2018.8406993"},{"issue":"3","key":"9895_CR36","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1007\/s10922-024-09823-x","volume":"32","author":"JPM Santana","year":"2024","unstructured":"Santana, J.P.M., Abr\u00e3o, T.: Power-Profile in Q-Learning NOMA random access protocols for throughput maximization. J. Netw. Syst. Manag. 32(3), 48 (2024). https:\/\/doi.org\/10.1007\/s10922-024-09823-x","journal-title":"J. Netw. Syst. Manag."},{"key":"9895_CR37","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1016\/j.comcom.2021.04.020","volume":"174","author":"MR Palas","year":"2021","unstructured":"Palas, M.R., Islam, M.R., Roy, P., et al.: Multi-criteria handover mobility management in 5G cellular network. Comput. Commun. 174, 81\u201391 (2021). https:\/\/doi.org\/10.1016\/j.comcom.2021.04.020","journal-title":"Comput. Commun."},{"key":"9895_CR38","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2024.3357702","author":"A Alizadeh","year":"2024","unstructured":"Alizadeh, A., Lim, B., Vu, M.: Multi-Agent Q-Learning for real-time load balancing user association and handover in mobile networks. IEEE Trans. Wirel. Commun. (2024). https:\/\/doi.org\/10.1109\/TWC.2024.3357702","journal-title":"IEEE Trans. Wirel. Commun."},{"issue":"3","key":"9895_CR39","doi-asserted-by":"publisher","first-page":"630","DOI":"10.1109\/TNET.2011.2120618","volume":"19","author":"I Rhee","year":"2011","unstructured":"Rhee, I., Shin, M., Hong, S., et al.: On the Levy-Walk nature of human mobility. IEEE\/ACM Trans. Netw. 19(3), 630\u2013643 (2011). https:\/\/doi.org\/10.1109\/TNET.2011.2120618","journal-title":"IEEE\/ACM Trans. Netw."},{"key":"9895_CR40","doi-asserted-by":"publisher","first-page":"86495","DOI":"10.1109\/ACCESS.2020.2992805","volume":"8","author":"T Mumtaz","year":"2020","unstructured":"Mumtaz, T., Muhammad, S., Aslam, M.I., et al.: Dual Connectivity-Based Mobility Management and Data Split Mechanism in 4G\/5G Cellular Networks. IEEE Access 8, 86495\u201386509 (2020). https:\/\/doi.org\/10.1109\/ACCESS.2020.2992805","journal-title":"IEEE Access"},{"key":"9895_CR41","doi-asserted-by":"publisher","unstructured":"Islam, N., Kandeepan, S., Chavez, K.G., et\u00a0al.: A MDP-based Energy Efficient and Delay Aware Handover Algorithm. In: 2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS), IEEE, pp. 1\u20135 (2019). https:\/\/doi.org\/10.1109\/ICSPCS47537.2019.9008697","DOI":"10.1109\/ICSPCS47537.2019.9008697"},{"key":"9895_CR42","doi-asserted-by":"publisher","unstructured":"Campbell, J.S., Givigi, S.N., Schwartz, H.M.: Multiple-model Q-learning for stochastic reinforcement delays. In: 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), IEEE, pp. 1611\u20131617 (2014). https:\/\/doi.org\/10.1109\/SMC.2014.6974146","DOI":"10.1109\/SMC.2014.6974146"},{"key":"9895_CR43","doi-asserted-by":"publisher","unstructured":"Wu, M., Huang, W., Sun, K., et\u00a0al.: A DQN-Based Handover Management for SDN-Enabled Ultra-Dense Networks. In: 2020 IEEE 92nd Vehicular Technology Conference (VTC2020-Fall), IEEE, pp. 1\u20136 (2020). https:\/\/doi.org\/10.1109\/VTC2020-Fall49728.2020.9348779","DOI":"10.1109\/VTC2020-Fall49728.2020.9348779"},{"key":"9895_CR44","doi-asserted-by":"publisher","unstructured":"Wei, Y., Lung, C.H., Ajila, S., et\u00a0al.: Deep Q-Networks Assisted Pre-connect Handover Management for 5G Networks. In: 2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring), IEEE, pp. 1\u20136 (2023). https:\/\/doi.org\/10.1109\/VTC2023-Spring57618.2023.10199527","DOI":"10.1109\/VTC2023-Spring57618.2023.10199527"}],"container-title":["Journal of Network and Systems Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10922-024-09895-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10922-024-09895-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10922-024-09895-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,28]],"date-time":"2025-01-28T23:21:22Z","timestamp":1738106482000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10922-024-09895-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,20]]},"references-count":44,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["9895"],"URL":"https:\/\/doi.org\/10.1007\/s10922-024-09895-9","relation":{},"ISSN":["1064-7570","1573-7705"],"issn-type":[{"value":"1064-7570","type":"print"},{"value":"1573-7705","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,20]]},"assertion":[{"value":"21 August 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 November 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 November 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 December 2024","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"17"}}