{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T15:28:04Z","timestamp":1772119684634,"version":"3.50.1"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T00:00:00Z","timestamp":1761868800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T00:00:00Z","timestamp":1761868800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Netw Syst Manage"],"published-print":{"date-parts":[[2026,1]]},"DOI":"10.1007\/s10922-025-09992-3","type":"journal-article","created":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T07:33:41Z","timestamp":1761896021000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Priority-Aware Resource Reallocation in Edge Computing Using Reinforcement Learning"],"prefix":"10.1007","volume":"34","author":[{"given":"Sudabeh","family":"Mohammadi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Behzad","family":"Akbari","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,10,31]]},"reference":[{"key":"9992_CR1","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1016\/j.comcom.2021.09.003","volume":"180","author":"M Laroui","year":"2021","unstructured":"Laroui, M., Nour, B., Moungla, H., Cherif, M.A., Afifi, H., Guizani, M.: Edge and fog computing for iot: a survey on current research activities and future directions. Comput. Commun. 180, 210\u2013231 (2021). https:\/\/doi.org\/10.1016\/j.comcom.2021.09.003","journal-title":"Comput. Commun."},{"issue":"9","key":"9992_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3555802","volume":"55","author":"H Hua","year":"2023","unstructured":"Hua, H., Li, Y., Wang, T., Dong, N., Li, W., Cao, J.: Edge computing with artificial intelligence: a machine learning perspective. ACM Comput. Surv. 55(9), 1\u201335 (2023). https:\/\/doi.org\/10.1145\/3555802","journal-title":"ACM Comput. Surv."},{"issue":"2","key":"9992_CR3","doi-asserted-by":"publisher","first-page":"544","DOI":"10.1016\/j.jksuci.2023.01.001","volume":"35","author":"Z Sharif","year":"2023","unstructured":"Sharif, Z., Tang Jung, L., Ayaz, M., Yahya, M., Pitafi, S.: Priority-based task scheduling and resource allocation in edge computing for health monitoring system. J. King Saud Univ. - Comput. Inf. Sci. 35(2), 544\u2013559 (2023). https:\/\/doi.org\/10.1016\/j.jksuci.2023.01.001","journal-title":"J. King Saud Univ. - Comput. Inf. Sci."},{"key":"9992_CR4","doi-asserted-by":"publisher","unstructured":"Kurt, F.M., zg vde, B.A.: Edge computing for computer games by offloading physics computation. Gazi Univ. J. Sci. Part A: Eng. Innov. 10(3):310\u2013326 (2023). https:\/\/doi.org\/10.54287\/gujsa.1338594","DOI":"10.54287\/gujsa.1338594"},{"issue":"12","key":"9992_CR5","doi-asserted-by":"publisher","first-page":"2700","DOI":"10.3390\/electronics12122700","volume":"12","author":"S-M Chuang","year":"2023","unstructured":"Chuang, S.-M., Chen, C.-S., Wu, E.H.-K.: The implementation of interactive vr application and caching strategy design on mobile edge computing (mec). Electronics 12(12), 2700 (2023). https:\/\/doi.org\/10.3390\/electronics12122700","journal-title":"Electronics"},{"issue":"4","key":"9992_CR6","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1109\/IOTM.001.2200268","volume":"6","author":"E Karimi","year":"2023","unstructured":"Karimi, E., Chen, Y., Akbari, B.: Intelligent and decentralized resource allocation in vehicular edge computing networks. IEEE Internet Things Mag. 6(4), 112\u2013117 (2023). https:\/\/doi.org\/10.1109\/IOTM.001.2200268","journal-title":"IEEE Internet Things Mag."},{"key":"9992_CR7","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1016\/j.comcom.2022.04.006","volume":"189","author":"E Karimi","year":"2022","unstructured":"Karimi, E., Chen, Y., Akbari, B.: Task offloading in vehicular edge computing networks via deep reinforcement learning. Comput. Commun. 189, 193\u2013204 (2022). https:\/\/doi.org\/10.1016\/j.comcom.2022.04.006","journal-title":"Comput. Commun."},{"key":"9992_CR8","doi-asserted-by":"publisher","unstructured":"Huang, L., Feng, X., Qian, L., Wu, Y.: Deep reinforcement learning-based task offloading and resource allocation for mobile edge computing. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering 251, 33\u201342 (2018). https:\/\/doi.org\/10.1234\/example","DOI":"10.1234\/example"},{"issue":"4","key":"9992_CR9","doi-asserted-by":"publisher","first-page":"3415","DOI":"10.1109\/JIOT.2020.2970110","volume":"7","author":"X Liu","year":"2020","unstructured":"Liu, X., Yu, J., Wang, J., Gao, Y.: Resource allocation with edge computing in iot networks via machine learning. IEEE Internet Things 7(4), 3415\u20133426 (2020). https:\/\/doi.org\/10.1109\/JIOT.2020.2970110","journal-title":"IEEE Internet Things"},{"issue":"4","key":"9992_CR10","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1007\/s10723-023-09708-4","volume":"21","author":"X Gao","year":"2023","unstructured":"Gao, X., Ang, M.C., Althubiti, S.A.: Deep reinforcement learning and markov decision problem for task offloading in mobile edge computing. J. Grid Comput. 21(4), 78 (2023). https:\/\/doi.org\/10.1007\/s10723-023-09708-4","journal-title":"J. Grid Comput."},{"key":"9992_CR11","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1016\/j.future.2023.10.012","volume":"152","author":"Z Wang","year":"2024","unstructured":"Wang, Z., Goudarzi, M., Gong, M., Buyya, R.: Deep reinforcement learning-based scheduling for optimizing system load and response time in edge and fog computing environments. Future Gener. Comput. Syst. 152, 55\u201369 (2024). https:\/\/doi.org\/10.1016\/j.future.2023.10.012","journal-title":"Future Gener. Comput. Syst."},{"key":"9992_CR12","unstructured":"Engstrom, L., Ilyas, A., Santurkar, S., Tsipras, D., Janoos, F., Rudolph, L., Madry, A.: Implementation matters in deep rl: a case study on ppo and trpo. In: International Conference on Learning Representations (2020). https:\/\/openreview.net\/forum?id=r1etN1rtPB"},{"issue":"4","key":"9992_CR13","doi-asserted-by":"publisher","first-page":"2494","DOI":"10.1109\/JIOT.2020.3022699","volume":"8","author":"I Martinez","year":"2021","unstructured":"Martinez, I., Hafid, A.S., Jarray, A.: Design, resource management, and evaluation of fog computing systems: a survey. IEEE Internet Things J. 8(4), 2494\u20132516 (2021). https:\/\/doi.org\/10.1109\/JIOT.2020.3022699","journal-title":"IEEE Internet Things J."},{"issue":"1","key":"9992_CR14","doi-asserted-by":"publisher","first-page":"83","DOI":"10.23919\/JCN.2021.000041","volume":"24","author":"H Tran-Dang","year":"2022","unstructured":"Tran-Dang, H., Bhardwaj, S., Rahim, T., Musaddiq, A., Kim, D.-S.: Reinforcement learning based resource management for fog computing environment: lliterature review, challenges, and open issues. J. Commun. Netw. 24(1), 83\u201398 (2022). https:\/\/doi.org\/10.23919\/JCN.2021.000041","journal-title":"J. Commun. Netw."},{"issue":"6","key":"9992_CR15","doi-asserted-by":"publisher","first-page":"1162","DOI":"10.1016\/j.icte.2023.06.006","volume":"9","author":"MD Hossain","year":"2023","unstructured":"Hossain, M.D., Sultana, T., Akhter, S., Hossain, M.I., Thu, N.T., Huynh, L.N.T., Lee, G.-W., Huh, E.-N.: The role of microservice approach in edge computing: opportunities, challenges, and research directions. ICT Express 9(6), 1162\u20131182 (2023). https:\/\/doi.org\/10.1016\/j.icte.2023.06.006","journal-title":"ICT Express"},{"issue":"1","key":"9992_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3604933","volume":"56","author":"Z Ning","year":"2023","unstructured":"Ning, Z., Hu, H., Wang, X., Guo, L., Guo, S., Wang, G., Gao, X.: Mobile edge computing and machine learning in the internet of unmanned aerial vehicles: a survey. ACM Comput. Surv. 56(1), 1\u201331 (2023). https:\/\/doi.org\/10.1145\/3604933","journal-title":"ACM Comput. Surv."},{"issue":"13","key":"9992_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3589639","volume":"55","author":"X Zhang","year":"2023","unstructured":"Zhang, X., Debroy, S.: Resource management in mobile edge computing: a comprehensive survey. ACM Comput. Sureys 55(13), 1\u201337 (2023). https:\/\/doi.org\/10.1145\/3589639","journal-title":"ACM Comput. Sureys"},{"key":"9992_CR18","doi-asserted-by":"publisher","unstructured":"Raeisi-Varzaneh, M., Dakkak, O., Habbal, A., Kim, B.-S.: Resource scheduling in edge computing: architecture, taxonomy, open issues and future research directions. IEEE Access 11:25329\u201325350 (2023). https:\/\/doi.org\/10.1109\/ACCESS.2023.3256522","DOI":"10.1109\/ACCESS.2023.3256522"},{"key":"9992_CR19","doi-asserted-by":"publisher","unstructured":"Zolghadri, M., Asghari, P., Dashti, S.E., Hedayati, A.: Resource allocation in fog cloud environments: state of the art. J. Netw. Comput. Appl. 227 (2024). https:\/\/doi.org\/10.1016\/j.jnca.2024.103891e","DOI":"10.1016\/j.jnca.2024.103891e"},{"issue":"1","key":"9992_CR20","doi-asserted-by":"publisher","first-page":"619","DOI":"10.1109\/COMST.2023.3338015","volume":"26","author":"GK Walia","year":"2024","unstructured":"Walia, G.K., Kumar, M., Gill, S.S.: Ai-empowered fog\/edge resource management for iot applications: a comprehensive review, research challenges, and future perspectives. IEEE Commun. Surveys Tutorials 26(1), 619\u2013669 (2024). https:\/\/doi.org\/10.1109\/COMST.2023.3338015","journal-title":"IEEE Commun. Surveys Tutorials"},{"issue":"2","key":"9992_CR21","doi-asserted-by":"publisher","first-page":"450","DOI":"10.1016\/j.dcan.2022.03.003","volume":"9","author":"K Sadatdiynov","year":"2023","unstructured":"Sadatdiynov, K., Cui, L., Zhang, L., Huang, J.Z., Salloum, S., Mahmud, M.S.: A review of optimization methods for computation offloading in edge computing networks. Digital Commun. Netw. 9(2), 450\u2013461 (2023). https:\/\/doi.org\/10.1016\/j.dcan.2022.03.003","journal-title":"Digital Commun. Netw."},{"issue":"8","key":"9992_CR22","doi-asserted-by":"publisher","first-page":"23019","DOI":"10.1007\/s11042-023-16399-2","volume":"83","author":"M Fahimullah","year":"2024","unstructured":"Fahimullah, M., Ahvar, S., Agarwal, M., Trocan, M.: Machine learning-based solutions for resource management in fog computing. Multimedia Tools Appl. 83(8), 23019\u201323045 (2024). https:\/\/doi.org\/10.1007\/s11042-023-16399-2","journal-title":"Multimedia Tools Appl."},{"issue":"1","key":"9992_CR23","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1109\/TMC.2022.3213410","volume":"23","author":"NM Laboni","year":"2024","unstructured":"Laboni, N.M., Safa, S.J., Sharmin, S., Razzaque, M.A., Rahman, M.M., Hassan, M.M.: A hyper heuristic algorithm for efficient resource allocation in 5g mobile edge clouds. IEEE Trans. Mob. Comput. 23(1), 29\u201341 (2024). https:\/\/doi.org\/10.1109\/TMC.2022.3213410","journal-title":"IEEE Trans. Mob. Comput."},{"key":"9992_CR24","doi-asserted-by":"publisher","unstructured":"Hortelano, D., de Miguel, I., Barroso, R.J.D., Aguado, J.C., Merayo, N., Ruiz, L., Asensio, A., Masip-Bruin, X., Fern ndez, P., Lorenzo, R.M., Abril, E.J.: A comprehensive survey on reinforcement-learning-based computation offloading techniques in edge computing systems. J. Netw. Comput. Appl. 216 (2023). https:\/\/doi.org\/10.1016\/j.jnca.2023.103669","DOI":"10.1016\/j.jnca.2023.103669"},{"key":"9992_CR25","doi-asserted-by":"publisher","unstructured":"Anoushee, M., Fartash, M., Akbari\u00a0Torkestani, J.: An intelligent resource management method in sdn based fog computing using reinforcement learning. Computing 106, 1051\u20131080 (2024). https:\/\/doi.org\/10.1007\/s00607-022-01141-x","DOI":"10.1007\/s00607-022-01141-x"},{"key":"9992_CR26","doi-asserted-by":"publisher","unstructured":"Ocampo, A.F., Santos, J.: Reinforcement learning-driven service placement in 6g networks across the compute continuum. In: 2024 20th International Conference on Network and Service Management (CNSM), pp. 1\u20139 (2024). https:\/\/doi.org\/10.23919\/CNSM62983.2024.10814365","DOI":"10.23919\/CNSM62983.2024.10814365"},{"issue":"2","key":"9992_CR27","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1016\/j.future.2022.05.021","volume":"136","author":"GL Santos","year":"2022","unstructured":"Santos, G.L., Endo, P.T., Lynn, T., Sadok, D., Kelner, J.: A reinforcement learning-based approach for availability-aware service function chain placement in large-scale networks. Future Gener. Comput. Syst. 136(2), 93\u2013109 (2022). https:\/\/doi.org\/10.1016\/j.future.2022.05.021","journal-title":"Future Gener. Comput. Syst."},{"key":"9992_CR28","doi-asserted-by":"publisher","unstructured":"Santos, J., Zaccarini, M., Poltronieri, F., Tortonesi, M., Stefanelli, C., Di Cicco, N., De Turck, F.: Hephaestusforge: optimal microservice deployment across the compute continuum via reinforcement learning. Future Gener. Comput. Syst. 166, 107680 (2025). https:\/\/doi.org\/10.1016\/j.future.2024.107680","DOI":"10.1016\/j.future.2024.107680"},{"key":"9992_CR29","doi-asserted-by":"publisher","unstructured":"Khani, M., Sadr, M.M., Jamali, S.: Deep reinforcement learning-based resource allocation in multi-access edge computing. Concurr. Comput.: Pract. Exp. 36(15) (2024). https:\/\/doi.org\/10.1002\/cpe.7995","DOI":"10.1002\/cpe.7995"},{"key":"9992_CR30","doi-asserted-by":"publisher","unstructured":"Zhou, X., Yang, J., Li, Y., Li, S., Su, Z.: Deep reinforcement learning-based resource scheduling for energy optimization and load balancing in sdn-driven edge computing. Comput. Commun. 226, 227 (2024). https:\/\/doi.org\/10.1016\/j.comcom.2024.107925","DOI":"10.1016\/j.comcom.2024.107925"},{"key":"9992_CR31","doi-asserted-by":"publisher","unstructured":"Zhou, G., Tian, W., Buyya, R., Xue, R., Song, L.: Deep reinforcement learning-based methods for resource scheduling in cloud computing: a review and future directions. Artif. Intell. Rev. 57, 124 (2024). https:\/\/doi.org\/10.1007\/s10462-024-10756-9","DOI":"10.1007\/s10462-024-10756-9"},{"issue":"4","key":"9992_CR32","doi-asserted-by":"publisher","first-page":"3043","DOI":"10.1109\/TSC.2022.3218044","volume":"16","author":"M Bansal","year":"2023","unstructured":"Bansal, M., Chana, I., Clarke, S.: Urbanenqosplace: a deep reinforcement learning model for service placement of real-time smart city iot applications. IEEE Trans. Serv. Comput. 16(4), 3043\u20133060 (2023). https:\/\/doi.org\/10.1109\/TSC.2022.3218044","journal-title":"IEEE Trans. Serv. Comput."},{"issue":"7","key":"9992_CR33","doi-asserted-by":"publisher","first-page":"3870","DOI":"10.1109\/TMC.2022.3148254","volume":"22","author":"T Liu","year":"2023","unstructured":"Liu, T., Ni, S., Li, X., Zhu, Y., Kong, L., Yang, Y.: Deep reinforcement learning based approach for online service placement and computation resource allocation in edge computing. IEEE Trans. Mob. Comput. 22(7), 3870\u20133881 (2023). https:\/\/doi.org\/10.1109\/TMC.2022.3148254","journal-title":"IEEE Trans. Mob. Comput."},{"issue":"6","key":"9992_CR34","doi-asserted-by":"publisher","first-page":"9717","DOI":"10.1109\/TVT.2025.3540964","volume":"74","author":"J Li","year":"2025","unstructured":"Li, J., Shi, Y., Dai, C., Yi, C., Yang, Y., Zhai, X., Zhu, K.: A learning-based stochastic game for energy efficient optimization of uav trajectory and task offloading in space\/aerial edge computing. IEEE Trans. Veh. Technol. 74(6), 9717\u20139733 (2025). https:\/\/doi.org\/10.1109\/TVT.2025.3540964","journal-title":"IEEE Trans. Veh. Technol."},{"issue":"1","key":"9992_CR35","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1109\/TGCN.2024.3424449","volume":"9","author":"J Li","year":"2025","unstructured":"Li, J., Yi, C., Chen, J., Shi, Y., Zhang, T., Li, X., Wang, R., Zhu, K.: A reinforcement learning-based stochastic game for energy-efficient uav swarm-assisted mec with dynamic clustering and scheduling. IEEE Trans. Green Commun. Netw. 9(1), 255\u2013270 (2025). https:\/\/doi.org\/10.1109\/TGCN.2024.3424449","journal-title":"IEEE Trans. Green Commun. Netw."},{"issue":"43","key":"9992_CR36","doi-asserted-by":"publisher","first-page":"7011","DOI":"10.1007\/s10922-025-09918-z","volume":"33","author":"SK Ghosh","year":"2025","unstructured":"Ghosh, S.K., Vittamsetti, V.M.: Distributed maximum utility task offloading for delay-sensitive iot applications in cloud and edge computing. Netw. Syst. Manag. 33(43), 7011\u20137024 (2025). https:\/\/doi.org\/10.1007\/s10922-025-09918-z","journal-title":"Netw. Syst. Manag."},{"key":"9992_CR37","doi-asserted-by":"publisher","unstructured":"Shi, Y., Wang, J., Yi, C., Wang, R., Chen, B.: Proactive application deployment for mec: an adaptive optimization based on imperfect multi-dimensional prediction. IEEE Trans. Veh. Technol., pp. 1\u201316 (2025). https:\/\/doi.org\/10.1109\/TVT.2025.3572680","DOI":"10.1109\/TVT.2025.3572680"},{"key":"9992_CR38","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1016\/j.comcom.2023.07.023","volume":"209","author":"G Baranwal","year":"2023","unstructured":"Baranwal, G., Kumar, D., Vidyarthi, D.P.: Blockchain based resource allocation in cloud and distributed edge computing: a survey. Comput. Commun. 209, 469\u2013498 (2023). https:\/\/doi.org\/10.1016\/j.comcom.2023.07.023","journal-title":"Comput. Commun."},{"issue":"6","key":"9992_CR39","doi-asserted-by":"publisher","first-page":"2761","DOI":"10.1109\/TNET.2023.3263538","volume":"31","author":"LT Hoang","year":"2023","unstructured":"Hoang, L.T., Nguyen, C.T., Pham, A.T.: Deep reinforcement learning-based online resource management for uav-assisted edge computing with dual connectivity. IEEE\/ACM Trans. Netw. 31(6), 2761\u20132776 (2023). https:\/\/doi.org\/10.1109\/TNET.2023.3263538","journal-title":"IEEE\/ACM Trans. Netw."},{"issue":"13","key":"9992_CR40","doi-asserted-by":"publisher","first-page":"23370","DOI":"10.1109\/JIOT.2024.3385816","volume":"11","author":"Y Shi","year":"2024","unstructured":"Shi, Y., Yang, Y., Yi, C., Chen, B., Cai, J.: Toward online reliability-enhanced microservice deployment with layer sharing in edge computing. IEEE Internet Things J. 11(13), 23370\u201323383 (2024). https:\/\/doi.org\/10.1109\/JIOT.2024.3385816","journal-title":"IEEE Internet Things J."},{"key":"9992_CR41","doi-asserted-by":"publisher","unstructured":"Zheng, Y., Cui, L., Tso, F.P., Li, Z., Jia, W.: Dnn acceleration in vehicle edge computing with mobility-awareness: a synergistic vehicle edge and edge edge framework. Comput. Netw. 251 (2024). https:\/\/doi.org\/10.1016\/j.comnet.2024.110607","DOI":"10.1016\/j.comnet.2024.110607"},{"issue":"40","key":"9992_CR42","doi-asserted-by":"publisher","first-page":"3479","DOI":"10.1109\/TNSE.2024.3375374","volume":"11","author":"Y Chen","year":"2024","unstructured":"Chen, Y., Sun, Y., Yu, H., Taleb, T.: Joint task and computing resource allocation in distributed edge computing systems via multi-agent deep reinforcement learning. IEEE Trans. Netw. Sci. Eng. 11(40), 3479\u20133494 (2024). https:\/\/doi.org\/10.1109\/TNSE.2024.3375374","journal-title":"IEEE Trans. Netw. Sci. Eng."},{"issue":"2","key":"9992_CR43","doi-asserted-by":"publisher","first-page":"1503","DOI":"10.1109\/TWC.2023.3290005","volume":"23","author":"Y Shi","year":"2024","unstructured":"Shi, Y., Yi, C., Wang, R., Wu, Q., Chen, B., Cai, J.: Service migration or task rerouting: a two-timescale online resource optimization for mec. IEEE Trans. Wirel. Commun. 23(2), 1503\u20131519 (2024). https:\/\/doi.org\/10.1109\/TWC.2023.3290005","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"9992_CR44","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.comcom.2023.02.001","volume":"202","author":"Z Peng","year":"2023","unstructured":"Peng, Z., Wang, G., Nong, W., Yu, Q., Huang, S.: Task offloading in multiple-services mobile edge computing: a deep reinforcement learning algorithm. Comput. Commun. 202, 1\u201312 (2023). https:\/\/doi.org\/10.1016\/j.comcom.2023.02.001","journal-title":"Comput. Commun."},{"key":"9992_CR45","doi-asserted-by":"publisher","unstructured":"Gargari, A.A., Pagin, M., Polese, M., Zorzi, M.: 6g integrated access and backhaul networks with sub-terahertz links. In: 2023 18th Wireless On-Demand Network Systems and Services Conference (WONS), pp. 13\u201319 (2023). https:\/\/doi.org\/10.23919\/WONS57325.2023.10061913","DOI":"10.23919\/WONS57325.2023.10061913"},{"issue":"5","key":"9992_CR46","doi-asserted-by":"publisher","first-page":"5321","DOI":"10.1109\/TNSM.2024.3392857","volume":"21","author":"D Tipper","year":"2024","unstructured":"Tipper, D., Babay, A., Palanisamy, B., Krishnamurthy, P.: Network connectivity resilience in next generation backhaul networks: challenges and future opportunities. IEEE Trans. Netw. Serv. Manage. 21(5), 5321\u20135334 (2024). https:\/\/doi.org\/10.1109\/TNSM.2024.3392857","journal-title":"IEEE Trans. Netw. Serv. Manage."},{"issue":"1","key":"9992_CR47","doi-asserted-by":"publisher","first-page":"372","DOI":"10.1109\/TSC.2019.2944360","volume":"15","author":"K Fizza","year":"2019","unstructured":"Fizza, K., Auluck, N., Azim, A.: Improving the schedulability of real-time tasks using fog computing. IEEE Trans. Serv. Comput. 15(1), 372\u2013385 (2019). https:\/\/doi.org\/10.1109\/TSC.2019.2944360","journal-title":"IEEE Trans. Serv. Comput."},{"key":"9992_CR48","doi-asserted-by":"publisher","unstructured":"Abdi, S., Ashjaei, S.M.H., Mubeen, S.: Task offloading in edge-cloud computing using a q-learning algorithm. In: 14th International Conference on Cloud Computing and Services Science (CLOSER), pp. 159\u2013166 (2024). https:\/\/doi.org\/10.5220\/0012590800003711","DOI":"10.5220\/0012590800003711"},{"key":"9992_CR49","doi-asserted-by":"publisher","first-page":"580","DOI":"10.3233\/ATDE250294","volume":"70","author":"C Liu","year":"2025","unstructured":"Liu, C., Li, S., Shi, K., Chen, H., Li, S., Kanellopoulos, D.: Task scheduling and resource allocation based on reinforcement learning in edge computing. Intelli. Transport. Smart Cities 70, 580\u2013589 (2025). https:\/\/doi.org\/10.3233\/ATDE250294","journal-title":"Intelli. Transport. Smart Cities"}],"container-title":["Journal of Network and Systems Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10922-025-09992-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10922-025-09992-3","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10922-025-09992-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T03:13:28Z","timestamp":1769915608000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10922-025-09992-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,31]]},"references-count":49,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1]]}},"alternative-id":["9992"],"URL":"https:\/\/doi.org\/10.1007\/s10922-025-09992-3","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-6545669\/v1","asserted-by":"object"}]},"ISSN":["1064-7570","1573-7705"],"issn-type":[{"value":"1064-7570","type":"print"},{"value":"1573-7705","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,31]]},"assertion":[{"value":"28 April 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 August 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 October 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 October 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"20"}}