Ortiz, J.N., Diaz, P.R., Sendra, S., Ameigeiras, P., Ramos-Munoz, J.J., Lopez-Soler, J.M.: A survey on 5G usage scenarios and traffic models. IEEE Commun. Surv. Tutor. 22(2), 905–929 (2020)
Siriwardhana, Y., Porambage, P., Liyanage, M., Ylianttila, M.: A survey on mobile augmented reality with 5g mobile edge computing: architectures, applications, and technical aspects. IEEE Commun. Surv. Tutor. 23(2), 1160–1192 (2021)
Qiao, X., Ren, P., Dustdar, S., Liu, L., Ma, H., Chen, J.: Web AR: a promising future for mobile augmented reality-state of the art, challenges, and insights. Proc. IEEE 107(4), 651–666 (2019)
Fraga-Lamas, P., Fernández-Caramés, T.M., Blanco-Novoa, Ó., Vilar-Montesinos, M.A.: A review on industrial augmented reality systems for the industry 4.0 shipyard. IEEE Access 6, 13358–13375 (2018)
Dilekm, U., Erol, M.: Detecting position using ARKit. Phys. Educ. 53(2), 025011 (2018)
Series, M.: IMT vision-framework and overall objectives of the future development of IMT for 2020 and beyond, p. 2083. Recommendation ITU (2015)
Zhang, W., Han, B., Hui, P.: On the networking challenges of mobile augmented reality. In: Proceedings of the workshop on virtual reality and augmented reality network. ACM (2017)
Koutitas, G., Siddaraju, V.K., Metsis, V.: In situ wireless channel visualization using augmented reality and ray tracing. Sensors 20(3), 690 (2020)
Bastug, E., Bennis, M., Médard, M., Debbah, M.: Toward interconnected virtual reality: opportunities, challenges, and enablers. IEEE Commun. Mag. 55(6), 110–117 (2017)
Liu, Y., Ling, J., Shou, G., Seah, H.S., Hu, Y.: Augmented reality based on the integration of mobile edge computing and fiber-wireless access networks. In: Proceedings of the international workshop on advanced image technology (IWAIT). International Society for Optics and Photonics (2019)
Zaman, S.K.U., Jehangiri, A.I., Maqsood, T., et al.: Mobility-aware computational offloading in mobile edge networks: a survey. Cluster Comput 24, 2735–2756 (2021)
ETSI GR MEC 035 V3.1.1: Multi-access edge computing (MEC); study on inter-MEC systems and MEC-cloud systems coordination.
Li, S., Li, B., Zhao, W.: Joint optimization of caching and computation in multi-server NOMA-MEC system via reinforcement learning. IEEE Access 8, 112762–112771 (2020)
Sangaiah, A.K., Javadpour, A., Pinto, P., Ja’fari, F., Zhang, W.: Improving quality of service in 5G resilient communication with the cellular structure of smartphones. ACM Trans Sens Netw (TOSN) 18(3), 1–23 (2022)
Javadpour, A., Wang, G.: cTMvSDN: improving resource management using combination of Markov-process and TDMA in software-defined networking. J. Supercomput. 78(3), 3477–3499 (2022)
Ateya, A.A., Muthanna, A., Koucheryavy, A.: 5G framework based on multi-level edge computing with D2D enabled communication. In: Proceedings of the 20th international conference on advanced communication technology (ICACT), pp. 507–512. IEEE (2018)
Ateya, A.A., Muthanna, A., Gudkova, I., Abuarqoub, A., Vybornova, A., Koucheryavy, A.: Development of intelligent core network for tactile internet and future smart systems. J Sens Actuator Netw 7(1), 1 (2018)
Elbamby, M.S., Perfecto, C., Bennis, M., Doppler, K.: Toward low-latency and ultra-reliable virtual reality. IEEE Netw 32(2), 78–84 (2018)
Mota, J.M., Ruiz-Rube, I., Dodero, J.M., Arnedillo-Sánchez, I.: Augmented reality mobile app development for all. Comput. Electr. Eng. 65, 250–260 (2018)
Schmoll, R.S., Pandi, S., Braun, P.J., Fitzek, F.H.: Demonstration of VR/AR offloading to mobile edge cloud for low latency 5G gaming application. In: Proceedings of the 15th IEEE annual consumer communications & networking conference (CCNC), pp. 1–3. IEEE (2018)
Lo, W.C., Huang, C.Y., Hsu, C.H.: Edge-assisted rendering of 360° videos streamed to head-mounted virtual reality. In: Proceedings of the IEEE international symposium on multimedia (ISM), pp. 44–51. IEEE (2018)
Filali, A., Nour, B., Cherkaoui S., Kobbane, A.: Communication and computation O-RAN resource slicing for URLLC services using deep reinforcement learning. arXiv preprint, arXiv:2202.06439. (2022)
Zaman, S.K.U., Jehangiri, A.I., Maqsood, T., et al.: LiMPO: lightweight mobility prediction and offloading framework using machine learning for mobile edge computing. Cluster Comput (2022). https://doi.org/10.1007/s10586-021-03518-7
Pan, C., Wang, Z., Liao, H., Zhou, Z., Wang, X., Tariq, M., Al-Otaibi, S.: Asynchronous federated deep reinforcement learning-based URLLC-aware computation offloading in space-assisted vehicular networks. IEEE Trans Intell Transport Syst (2022). https://doi.org/10.1109/TITS.2022.3150756
Tabarsi, B.T., Rezaee, A., Movaghar, A.: ROGI: partial computation offloading and resource allocation in the fog-based IoT network towards optimizing latency and power consumption. Cluster Comput (2022). https://doi.org/10.1007/s10586-022-03710-3
Yun, J., Goh, Y., Yoo, W., Chung, J.M.: 5G Multi-RAT URLLC and eMBB dynamic task offloading with MEC resource allocation using distributed deep reinforcement learning. IEEE Internet Things J 2022, 1–10 (2022)
Keshavarznejad, M., Rezvani, M.H., Adabi, S.: Delay-aware optimization of energy consumption for task offloading in fog environments using metaheuristic algorithms. Cluster Comput 24, 1825–1853 (2021). https://doi.org/10.1007/s10586-020-03230-y
Ateya, A., Muthanna, A., Vybornova, A., Darya, P., Koucheryavy, A.: Energy—aware offloading algorithm for multi-level cloud based 5G system. In: Internet of things, smart spaces, and next generation networks and systems. Springer, Cham (2018)
Ateya, A.A., Muthanna, A., Vybornova, A., Algarni, A.D., Abuarqoub, A., Koucheryavy, Y., Koucheryavy, A.: Chaotic salp swarm algorithm for SDN multi-controller networks. Eng Sci Technol Int J 22(4), 1001–1012 (2019)
Mishra, V., Upadhyay, R., Bhatt, U.R., Kumar, A.: DEC TDMA: a delay controlled and energy efficient clustered TDMA mechanism for FiWi access network. Optik 225, 164921 (2021)
Ateya, A.A., Muthanna, A., Vybornova, A., Koucheryavy, A.: Multi-level cluster based device-to-device (d2d) communication protocol for the base station failure situation. In: Internet of things, smart spaces, and next generation networks and systems, pp. 755–765. Springer, Cham (2017)
Sankaran, L., Subramanian, S.J.: CloudSim exploration: a knowledge framework for cloud computing researchers. In: Applied soft computing and communication networks, pp. 107–122. Springer, Singapore (2021)