{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T00:08:14Z","timestamp":1784074094453,"version":"3.55.0"},"reference-count":59,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,1,11]],"date-time":"2022-01-11T00:00:00Z","timestamp":1641859200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,1,11]],"date-time":"2022-01-11T00:00:00Z","timestamp":1641859200000},"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":["Cluster Comput"],"published-print":{"date-parts":[[2023,2]]},"DOI":"10.1007\/s10586-021-03518-7","type":"journal-article","created":{"date-parts":[[2022,1,11]],"date-time":"2022-01-11T08:02:30Z","timestamp":1641888150000},"page":"99-117","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":80,"title":["LiMPO: lightweight mobility prediction and offloading framework using machine learning for mobile edge computing"],"prefix":"10.1007","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0261-6541","authenticated-orcid":false,"given":"Sardar Khaliq uz","family":"Zaman","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali Imran","family":"Jehangiri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tahir","family":"Maqsood","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nuhman ul","family":"Haq","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arif Iqbal","family":"Umar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junaid","family":"Shuja","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zulfiqar","family":"Ahmad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Imed Ben","family":"Dhaou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammed F.","family":"Alsharekh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,1,11]]},"reference":[{"key":"3518_CR1","first-page":"31","volume":"17","author":"J Wang","year":"2020","unstructured":"Wang, J., Lv, T., Huang, P., Mathiopoulos, P.T.: Mobility-aware partial computation offloading in vehicular networks: a deep reinforcement learning based scheme. China Commun. 17, 31\u201349 (2020)","journal-title":"China Commun."},{"key":"3518_CR2","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1007\/s12083-019-00721-7","volume":"13","author":"D Rahbari","year":"2020","unstructured":"Rahbari, D., Nickray, M.: Task offloading in mobile fog computing by classification and regression tree. Peer-to-Peer Netw. Appl. 13, 104\u2013122 (2020)","journal-title":"Peer-to-Peer Netw. Appl."},{"key":"3518_CR3","doi-asserted-by":"crossref","unstructured":"Dong, Q., Sinangil, M.E., Erbagci, B., Sun, D., Khwa, W.-S., Liao, H.-J., et al.: 15.3 A 351TOPS\/W and 372.4 GOPS compute-in-memory SRAM macro in 7nm FinFET CMOS for machine-learning applications. In: 2020 IEEE International Solid-State Circuits Conference-(ISSCC), pp. 242\u2013244 (2020)","DOI":"10.1109\/ISSCC19947.2020.9062985"},{"key":"3518_CR4","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1007\/978-3-319-34208-5_14","volume-title":"5G Mobile Communications","author":"IB Dhaou","year":"2017","unstructured":"Dhaou, I.B., Tenhunen, H.: Design techniques of 5G mobile devices in the dark silicon era. In: Xiang, W., Zheng, K. (eds.) 5G Mobile Communications, pp. 381\u2013400. Springer, Berlin (2017)"},{"key":"3518_CR5","doi-asserted-by":"publisher","first-page":"103005","DOI":"10.1016\/j.jnca.2021.103005","volume":"181","author":"J Shuja","year":"2021","unstructured":"Shuja, J., Bilal, K., Alasmary, W., Sinky, H., Alanazi, E.: Applying machine learning techniques for caching in next-generation edge networks: a comprehensive survey. J. Netw. Comput. Appl. 181, 103005 (2021)","journal-title":"J. Netw. Comput. Appl."},{"key":"3518_CR6","doi-asserted-by":"publisher","first-page":"29609","DOI":"10.1109\/ACCESS.2021.3059072","volume":"9","author":"M Babar","year":"2021","unstructured":"Babar, M., Khan, M.S., Ali, F., Imran, M., Shoaib, M.: Cloudlet computing: recent advances, taxonomy, and challenges. IEEE Access 9, 29609\u201329622 (2021)","journal-title":"IEEE Access"},{"key":"3518_CR7","doi-asserted-by":"publisher","first-page":"1896","DOI":"10.1002\/spe.2850","volume":"51","author":"SU Malik","year":"2020","unstructured":"Malik, S.U., Akram, H., Gill, S.S., Pervaiz, H., Malik, H.: EFFORT: energy efficient framework for offload communication in mobile cloud computing. Softw. Pract. Exp. 51, 1896 (2020)","journal-title":"Softw. Pract. Exp."},{"key":"3518_CR8","doi-asserted-by":"publisher","first-page":"54074","DOI":"10.1109\/ACCESS.2020.2981434","volume":"8","author":"T Alfakih","year":"2020","unstructured":"Alfakih, T., Hassan, M.M., Gumaei, A., Savaglio, C., Fortino, G.: Task offloading and resource allocation for mobile edge computing by deep reinforcement learning based on SARSA. IEEE Access 8, 54074\u201354084 (2020)","journal-title":"IEEE Access"},{"key":"3518_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3341145","volume":"52","author":"TL Duc","year":"2019","unstructured":"Duc, T.L., Leiva, R.G., Casari, P., \u00d6stberg, P.-O.: Machine learning methods for reliable resource provisioning in edge-cloud computing: a survey. ACM Comput. Surv. (CSUR) 52, 1\u201339 (2019)","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"3518_CR10","doi-asserted-by":"publisher","first-page":"1628","DOI":"10.1109\/COMST.2017.2682318","volume":"19","author":"P Mach","year":"2017","unstructured":"Mach, P., Becvar, Z.: Mobile edge computing: a survey on architecture and computation offloading. IEEE Commun. Surv. Tutor. 19, 1628\u20131656 (2017)","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"3518_CR11","doi-asserted-by":"crossref","unstructured":"Peng, Q., Xia, Y., Feng, Z., Lee, J., Wu, C., Luo, X., et al.: Mobility-aware and migration-enabled online edge user allocation in mobile edge computing. In: 2019 IEEE International Conference on Web Services (ICWS), pp. 91-98 (2019)","DOI":"10.1109\/ICWS.2019.00026"},{"key":"3518_CR12","doi-asserted-by":"publisher","first-page":"722","DOI":"10.1016\/j.future.2018.07.032","volume":"89","author":"F Yu","year":"2018","unstructured":"Yu, F., Chen, H., Xu, J.: DMPO: dynamic mobility-aware partial offloading in mobile edge computing. Future Gener. Comput. Syst. 89, 722\u2013735 (2018)","journal-title":"Future Gener. Comput. Syst."},{"key":"3518_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.future.2018.02.014","volume":"85","author":"Z Wang","year":"2018","unstructured":"Wang, Z., Zhao, Z., Min, G., Huang, X., Ni, Q., Wang, R.: User mobility aware task assignment for mobile edge computing. Future Gener. Comput. Syst. 85, 1\u20138 (2018)","journal-title":"Future Gener. Comput. Syst."},{"key":"3518_CR14","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-021-03376-3","author":"E Mustafa","year":"2021","unstructured":"Mustafa, E., Shuja, J., Jehangiri, A.I., Din, S., Rehman, F., Mustafa, S., et al.: Joint wireless power transfer and task offloading in mobile edge computing: a survey. Cluster Comput. (2021). https:\/\/doi.org\/10.1007\/s10586-021-03376-3","journal-title":"Cluster Comput."},{"key":"3518_CR15","doi-asserted-by":"publisher","first-page":"107496","DOI":"10.1016\/j.comnet.2020.107496","volume":"182","author":"A Shakarami","year":"2020","unstructured":"Shakarami, A., Ghobaei-Arani, M., Shahidinejad, A.: A survey on the computation offloading approaches in mobile edge computing: a machine learning-based perspective. Comput. Netw. 182, 107496 (2020)","journal-title":"Comput. Netw."},{"key":"3518_CR16","doi-asserted-by":"publisher","first-page":"102062","DOI":"10.1016\/j.simpat.2019.102062","volume":"101","author":"C Puliafito","year":"2020","unstructured":"Puliafito, C., Gon\u00e7alves, D.M., Lopes, M.M., Martins, L.L., Madeira, E., Mingozzi, E., et al.: MobFogSim: simulation of mobility and migration for fog computing. Simul. Modell. Pract. Theory 101, 102062 (2020)","journal-title":"Simul. Modell. Pract. Theory"},{"key":"3518_CR17","doi-asserted-by":"publisher","first-page":"3133","DOI":"10.1109\/COMST.2019.2916583","volume":"21","author":"NC Luong","year":"2019","unstructured":"Luong, N.C., Hoang, D.T., Gong, S., Niyato, D., Wang, P., Liang, Y.-C., et al.: Applications of deep reinforcement learning in communications and networking: a survey. IEEE Commun. Surv. Tutor. 21, 3133\u20133174 (2019)","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"3518_CR18","doi-asserted-by":"publisher","first-page":"1603","DOI":"10.1109\/TPDS.2020.3046737","volume":"32","author":"C Liu","year":"2020","unstructured":"Liu, C., Tang, F., Hu, Y., Li, K., Tang, Z., Li, K.: Distributed task migration optimization in MEC by extending multi-agent deep reinforcement learning approach. IEEE Trans. Parallel Distrib. Syst. 32, 1603\u20131614 (2020)","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"3518_CR19","first-page":"1","volume":"4","author":"SK uz Zaman","year":"2021","unstructured":"uz Zaman, S.K., Jehangiri, A.I., Maqsood, T., Ahmad, Z., Umar, A.I., Shuja, J., et al.: Mobility-aware computational offloading in mobile edge networks: a survey. Cluster Comput. 4, 1\u201322 (2021)","journal-title":"Cluster Comput."},{"key":"3518_CR20","doi-asserted-by":"crossref","unstructured":"Chamola, V., Tham, C.-K., Chalapathi, G.S.: Latency aware mobile task assignment and load balancing for edge cloudlets. In: 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), pp. 587\u2013592 (2017)","DOI":"10.1109\/PERCOMW.2017.7917628"},{"key":"3518_CR21","doi-asserted-by":"crossref","unstructured":"Alam, M.G.R., Tun, Y.K., Hong, C.S.: Multi-agent and reinforcement learning based code offloading in mobile fog. In: International Conference on Information Networking (ICOIN), pp. 285\u2013290 (2016)","DOI":"10.1109\/ICOIN.2016.7427078"},{"key":"3518_CR22","doi-asserted-by":"publisher","first-page":"1272","DOI":"10.1109\/TNET.2019.2916577","volume":"27","author":"S Wang","year":"2019","unstructured":"Wang, S., Urgaonkar, R., Zafer, M., He, T., Chan, K., Leung, K.K.: Dynamic service migration in mobile edge computing based on Markov decision process. IEEE\/ACM Trans. Netw. 27, 1272\u20131288 (2019)","journal-title":"IEEE\/ACM Trans. Netw."},{"key":"3518_CR23","doi-asserted-by":"publisher","first-page":"1051","DOI":"10.1109\/TCSS.2019.2909265","volume":"6","author":"X Xia","year":"2019","unstructured":"Xia, X., Zhou, Y., Li, J., Yu, R.: Quality-aware sparse data collection in MEC-enhanced mobile crowdsensing systems. IEEE Trans. Comput. Soc. Syst. 6, 1051\u20131062 (2019)","journal-title":"IEEE Trans. Comput. Soc. Syst."},{"key":"3518_CR24","doi-asserted-by":"publisher","first-page":"3317","DOI":"10.1109\/TPDS.2014.2381640","volume":"26","author":"S Deng","year":"2015","unstructured":"Deng, S., Huang, L., Taheri, J., Zomaya, A.Y.: Computation offloading for service workflow in mobile cloud computing. IEEE Trans. Parallel Distrib. Syst. 26, 3317\u20133329 (2015)","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"3518_CR25","unstructured":"Waqas, M., Niu, Y., Li, Y., Ahmed, M., Jin, D., Chen, S., et al.: Mobility-aware device-to-device communications: principles, practice and challenges. In: IEEE Communications Surveys Tutorials, June 2019"},{"key":"3518_CR26","doi-asserted-by":"crossref","unstructured":"Lai, P., He, Q., Abdelrazek, M., Chen, F., Hosking, J., Grundy, J., et al.: Optimal edge user allocation in edge computing with variable sized vector bin packing. In: International Conference on Service-Oriented Computing, pp. 230\u2013245 (2018)","DOI":"10.1007\/978-3-030-03596-9_15"},{"key":"3518_CR27","doi-asserted-by":"crossref","unstructured":"Xu, J., Li, X., Liu, X., Zhang, C., Fan, L., Gong, L., et al.: Mobility-aware workflow offloading and scheduling strategy for mobile edge computing. In: International Conference on Algorithms and Architectures for Parallel Processing, pp. 184\u2013199 (2019)","DOI":"10.1007\/978-3-030-38961-1_17"},{"key":"3518_CR28","doi-asserted-by":"crossref","unstructured":"Wu, C.-L., Chiu, T.-C., Wang, C.-Y., Pang, A.-C.: Mobility-aware deep reinforcement learning with glimpse mobility prediction in edge computing. In: ICC 2020\u20132020 IEEE International Conference on Communications (ICC), pp. 1\u20137 (2020)","DOI":"10.1109\/ICC40277.2020.9149185"},{"key":"3518_CR29","doi-asserted-by":"publisher","first-page":"107435","DOI":"10.1016\/j.comnet.2020.107435","volume":"182","author":"X Zhao","year":"2020","unstructured":"Zhao, X., Shi, Y., Chen, S.: MAESP: mobility aware edge service placement in mobile edge networks. Comput. Netw. 182, 107435 (2020)","journal-title":"Comput. Netw."},{"key":"3518_CR30","doi-asserted-by":"publisher","first-page":"2637","DOI":"10.1109\/JSAC.2017.2760160","volume":"35","author":"Y Sun","year":"2017","unstructured":"Sun, Y., Zhou, S., Xu, J.: EMM: energy-aware mobility management for mobile edge computing in ultra dense networks. IEEE J. Sel. Areas Commun. 35, 2637\u20132646 (2017)","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"3518_CR31","doi-asserted-by":"crossref","unstructured":"Wu, C., Peng, Q., Xia, Y., Lee, J.: Mobility-aware tasks offloading in mobile edge computing environment. In: 2019 Seventh International Symposium on Computing and Networking (CANDAR), pp. 204\u2013210 (2019)","DOI":"10.1109\/CANDAR.2019.00034"},{"key":"3518_CR32","doi-asserted-by":"crossref","unstructured":"Thananjeyan, S., Chan, C.A., Wong, E., Nirmalathas, A.: Mobility-aware energy optimization in hosts selection for computation offloading in multi-access edge computing. In: IEEE Open Journal of the Communications Society (2020)","DOI":"10.1109\/OJCOMS.2020.3008485"},{"key":"3518_CR33","doi-asserted-by":"crossref","unstructured":"Ghosh, S., Mukherjee, A., Ghosh, S.K., Buyya, R.: Mobi-IoST: mobility-aware cloud-fog-edge-iot collaborative framework for time-critical applications. In: IEEE Transactions on Network Science and Engineering (2019)","DOI":"10.1109\/TNSE.2019.2941754"},{"key":"3518_CR34","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1109\/MWC.001.1900427","volume":"27","author":"C Wang","year":"2020","unstructured":"Wang, C., Elliott, R.C., Feng, D., Krzymien, W.A., Zhang, S., Melzer, J.: A framework for MEC-enhanced small-cell HetNet with massive MIMO. IEEE Wirel. Commun. 27, 64\u201372 (2020)","journal-title":"IEEE Wirel. Commun."},{"key":"3518_CR35","first-page":"227","volume":"32","author":"AUR Khan","year":"2017","unstructured":"Khan, A.U.R., uz Zaman, S.K., Malik, S.U.R., Khan, A.N., Maqsood, T., Madani, S.A.: Formal verification and performance evaluation of task scheduling heuristics for Makespan optimization and workflow distribution in large-scale computing systems. Comput. Syst. Sci. Eng. 32, 227 (2017)","journal-title":"Comput. Syst. Sci. Eng."},{"key":"3518_CR36","doi-asserted-by":"crossref","unstructured":"Xu, C., Zheng, G., Zhao, X.: Energy-minimization task offloading and resource allocation for mobile edge computing in NOMA heterogeneous networks. In: IEEE Transactions on Vehicular Technology (2020)","DOI":"10.1109\/TVT.2020.3040645"},{"key":"3518_CR37","doi-asserted-by":"crossref","unstructured":"De Maio, V., Brandic, I.: First hop mobile offloading of dag computations. In: 2018 18th IEEE\/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), pp. 83\u201392 (2018)","DOI":"10.1109\/CCGRID.2018.00023"},{"key":"3518_CR38","first-page":"31","volume":"17","author":"D Wang","year":"2020","unstructured":"Wang, D., Tian, X., Cui, H., Liu, Z.: Reinforcement learning-based joint task offloading and migration schemes optimization in mobility-aware MEC network. China Commun. 17, 31\u201344 (2020)","journal-title":"China Commun."},{"key":"3518_CR39","first-page":"1","volume":"4","author":"E Grochowski","year":"2006","unstructured":"Grochowski, E., Annavaram, M.: Energy per instruction trends in Intel microprocessors. Technology@ Intel Mag 4, 1\u20138 (2006)","journal-title":"Technology@ Intel Mag"},{"key":"3518_CR40","doi-asserted-by":"publisher","first-page":"370","DOI":"10.1007\/s11227-017-2133-4","volume":"74","author":"SK Mishra","year":"2018","unstructured":"Mishra, S.K., Puthal, D., Sahoo, B., Jena, S.K., Obaidat, M.S.: An adaptive task allocation technique for green cloud computing. J. Supercomput. 74, 370\u2013385 (2018)","journal-title":"J. Supercomput."},{"key":"3518_CR41","doi-asserted-by":"publisher","first-page":"2666","DOI":"10.1109\/JSAC.2020.3007035","volume":"38","author":"T Bai","year":"2020","unstructured":"Bai, T., Pan, C., Deng, Y., Elkashlan, M., Nallanathan, A., Hanzo, L.: Latency minimization for intelligent reflecting surface aided mobile edge computing. IEEE J. Sel. Areas Commun. 38, 2666\u20132682 (2020)","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"3518_CR42","doi-asserted-by":"publisher","first-page":"2795","DOI":"10.1109\/TNET.2015.2487344","volume":"24","author":"X Chen","year":"2015","unstructured":"Chen, X., Jiao, L., Li, W., Fu, X.: Efficient multi-user computation offloading for mobile-edge cloud computing. IEEE\/ACM Trans. Netw. 24, 2795\u20132808 (2015)","journal-title":"IEEE\/ACM Trans. Netw."},{"key":"3518_CR43","doi-asserted-by":"publisher","first-page":"587","DOI":"10.1109\/JSAC.2018.2815360","volume":"36","author":"M Chen","year":"2018","unstructured":"Chen, M., Hao, Y.: Task offloading for mobile edge computing in software defined ultra-dense network. IEEE J. Sel. Areas Commun. 36, 587\u2013597 (2018)","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"3518_CR44","doi-asserted-by":"publisher","first-page":"79","DOI":"10.32604\/csse.2019.34.079","volume":"34","author":"SK uz Zaman","year":"2019","unstructured":"uz Zaman, S.K., Tahir Maqsood, M.A., Bilal, K.: A load balanced task scheduling heuristic for large-scale computing systems. Comput. Syst. Sci. Eng. 34, 79 (2019)","journal-title":"Comput. Syst. Sci. Eng."},{"key":"3518_CR45","doi-asserted-by":"crossref","unstructured":"R\u0103dulescu, C.Z., R\u0103dulescu, D.M.: A performance and power consumption analysis based on processor power models. In: 2020 12th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), pp. 1\u20134 (2020)","DOI":"10.1109\/ECAI50035.2020.9223124"},{"key":"3518_CR46","doi-asserted-by":"crossref","unstructured":"Daraghmeh, M., Al Ridhawi, I., Aloqaily, M., Jararweh, Y., Agarwal, A.: A power management approach to reduce energy consumption for edge computing servers. In: 2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC), pp. 259\u2013264 (2019)","DOI":"10.1109\/FMEC.2019.8795328"},{"key":"3518_CR47","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1109\/MCOM.2019.1800608","volume":"57","author":"B Cao","year":"2019","unstructured":"Cao, B., Zhang, L., Li, Y., Feng, D., Cao, W.: Intelligent offloading in multi-access edge computing: a state-of-the-art review and framework. IEEE Commun. Mag. 57, 56\u201362 (2019)","journal-title":"IEEE Commun. Mag."},{"key":"3518_CR48","doi-asserted-by":"publisher","first-page":"2282","DOI":"10.1109\/TWC.2019.2963829","volume":"19","author":"TM Duong","year":"2020","unstructured":"Duong, T.M., Kwon, S.: Vertical handover analysis for randomly deployed small cells in heterogeneous networks. IEEE Trans. Wirel. Commun. 19, 2282\u20132292 (2020)","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"3518_CR49","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1109\/MWC.001.1900241","volume":"27","author":"X Liu","year":"2020","unstructured":"Liu, X., Yu, J., Qi, H., Yang, J., Rong, W., Zhang, X., et al.: Learning to predict the mobility of users in mobile mmWave networks. IEEE Wirel. Commun. 27, 124\u2013131 (2020)","journal-title":"IEEE Wirel. Commun."},{"key":"3518_CR50","first-page":"3","volume":"160","author":"SB Kotsiantis","year":"2007","unstructured":"Kotsiantis, S.B., Zaharakis, I., Pintelas, P.: Supervised machine learning: a review of classification techniques. Emerg. Artif. Intell. Appl. Comput. Eng. 160, 3\u201324 (2007)","journal-title":"Emerg. Artif. Intell. Appl. Comput. Eng."},{"key":"3518_CR51","doi-asserted-by":"publisher","first-page":"102974","DOI":"10.1016\/j.jnca.2021.102974","volume":"178","author":"A Shakarami","year":"2021","unstructured":"Shakarami, A., Shahidinejad, A., Ghobaei-Arani, M.: An autonomous computation offloading strategy in mobile edge computing: a deep learning-based hybrid approach. J. Netw. Comput. Appl. 178, 102974 (2021)","journal-title":"J. Netw. Comput. Appl."},{"key":"3518_CR52","first-page":"V2","volume":"36","author":"E. Access","year":"2010","unstructured":"E. Access: Further advancements for E-UTRA physical layer aspects. 3GPP Tech. Specif. TR 36, V2 (2010)","journal-title":"3GPP Tech. Specif. TR"},{"key":"3518_CR53","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1109\/TCOMM.2019.2949994","volume":"68","author":"W Wu","year":"2020","unstructured":"Wu, W., Zhou, F., Hu, R.Q., Wang, B.: Energy-efficient resource allocation for secure NOMA-enabled mobile edge computing networks. IEEE Trans. Commun. 68, 493\u2013505 (2020)","journal-title":"IEEE Trans. Commun."},{"key":"3518_CR54","doi-asserted-by":"crossref","unstructured":"Codeca, L., Frank, R., Engel, T.: Luxembourg sumo traffic (lust) scenario: 24 hours of mobility for vehicular networking research. In: 2015 IEEE Vehicular Networking Conference (VNC), pp. 1\u20138 (2015)","DOI":"10.1109\/VNC.2015.7385539"},{"key":"3518_CR55","doi-asserted-by":"crossref","unstructured":"Piri, E., Ruuska, P., Kanstr\u00e9n, T., M\u00e4kel\u00e4, J., Korva, J., Hekkala, A. et al.: 5GTN: A test network for 5G application development and testing. In: 2016 European Conference on Networks and Communications (EuCNC), pp. 313\u2013318 (2016)","DOI":"10.1109\/EuCNC.2016.7561054"},{"key":"3518_CR56","first-page":"5917","volume":"5","author":"MA Lema","year":"2017","unstructured":"Lema, M.A., Laya, A., Mahmoodi, T., Cuevas, M., Sachs, J., Markendahl, J., et al.: Business case and technology analysis for 5G low latency applications. IEEE Access 5, 5917\u20135935 (2017)","journal-title":"IEEE Access"},{"key":"3518_CR57","first-page":"1","volume":"34","author":"SK uz Zaman","year":"2019","unstructured":"uz Zaman, S.K., Maqsood, T., Ali, M., Bilal, K., Madani, S.A., Khan, A.U.R.: A load balanced task scheduling heuristic for large-scale computing systems. Comput. Syst. Sci. Eng 34, 1\u201312 (2019)","journal-title":"Comput. Syst. Sci. Eng"},{"key":"3518_CR58","unstructured":"Hossain, M.K., Rahman, M., Hossain, A., Rahman, S.Y., Islam, M.M.: Active & idle virtual machine migration algorithm-a new ant colony optimization approach to consolidate virtual machines and ensure green cloud computing"},{"key":"3518_CR59","doi-asserted-by":"publisher","first-page":"437","DOI":"10.1007\/978-3-642-35289-8_26","volume-title":"Neural Networks: Tricks of the Trade","author":"Y Bengio","year":"2012","unstructured":"Bengio, Y.: Practical recommendations for gradient-based training of deep architectures. In: Montavon, G., Orr, G.B. (eds.) Neural Networks: Tricks of the Trade, pp. 437\u2013478. Springer, Berlin (2012)"}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-021-03518-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10586-021-03518-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-021-03518-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,27]],"date-time":"2023-02-27T14:14:30Z","timestamp":1677507270000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10586-021-03518-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,11]]},"references-count":59,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,2]]}},"alternative-id":["3518"],"URL":"https:\/\/doi.org\/10.1007\/s10586-021-03518-7","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"value":"1386-7857","type":"print"},{"value":"1573-7543","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,11]]},"assertion":[{"value":"6 July 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 December 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 December 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 January 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This is the author's own work not submitted anywhere else.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"NA.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}]}}