dc.identifier.citation | [1] Ayimba, C., Casari, P., and Mancuso, V. SQLR: Short-term memory Q-learning for elastic provisioning. IEEE Trans. Netw. Service Manag. 18, 2 (2021), 1850–1869. [2] Barmpounakis, S., Tsiatsios, G., Papadakis, M., Mitsianis, E., Koursioumpas, N., and Alonistioti, N. Collision avoidance in 5G using MEC and NFV: The vulnerable road user safety use case. Computer Networks 172 (2020), 107150. [3] Boban, M., Kousaridas, A., Manolakis, K., Eichinger, J., and Xu, W. Connected roads of the future: Use cases, requirements, and design considerations for vehicle- to-everything communications. IEEE Veh. Technol. Mag. 13, 3 (2018), 110–123. [4] Chen, M., Li, W., Fortino, G., Hao, Y., Hu, L., and Humar, I. A dynamic service migration mechanism in edge cognitive computing. ACM Trans. Internet Technol. 19, 2 (Apr. 2019). [5] Dressler, F., Klingler, F., Segata, M., and Lo Cigno, R. Cooperative driving and the tactile Internet. Proc. IEEE 107, 2 (2019), 436–446. [6] Krajzewicz, D., Hertkorn, G., Rössel, C., and Wagner, P. SUMO (simulation of urban mobility) - an open-source traffic simulation. In 4th Middle East Symposium on Simulation and Modelling (2002), A. Al-Akaidi, Ed., pp. 183–187. [7] Lauridsen,M.,Gimenez,L.C.,Rodriguez,I.,Sorensen,T.B.,andMogensen, P. From LTE to 5G for connected mobility. IEEE Commun. Mag. 55, 3 (2017), 156–162. [8] Nardini, G., Virdis, A., Stea, G., and Buono, A. SimuLTE-MEC: extending SimuLTE for multi-access edge computing. In Proc. OMNeT++ summit (2018). [9] Ouyang, T., Zhou, Z., and Chen, X. Follow me at the edge: Mobility-aware dynamic service placement for mobile edge computing. IEEE J. Sel. Areas Commun. 36, 10 (2018), 2333–2345. [10] Ploeg, J., Scheepers, B., van Nunen, E., van de Wouw, N., and Nijmeijer, H. Design and experimental evaluation of cooperative adaptive cruise control. In Proc. IEEE ITSC (2011), pp. 260–265. [11] Quadri, C., Mancuso, V., Ajmone Marsan, M., and Rossi, G. P. Platooning on the edge. In Proc. ACM MSWiM (2020). [12] Rajamani, R. Vehicle Dynamics and Control, 2nd ed. Springer, 2012. [13] Rajamani, R., Han-Shue Tan, Boon Kait Law, and Wei-Bin Zhang. Demon- stration of integrated longitudinal and lateral control for the operation of auto- mated vehicles in platoons. IEEE Trans. Control Syst. Technol. 8, 4 (2000), 695–708. [14] Salaht, F. A., Desprez, F., and Lebre, A. An overview of service placement problem in fog and edge computing. ACM Comput. Surv. 53, 3 (June 2020). [15] Santini,S.,Salvi,A.,Valente,A.S.,Pescapé,A.,Segata,M.,andLoCigno,R. A consensus-based approach for platooning with intervehicular communications and its validation in realistic scenarios. IEEE Trans. Veh. Technol. 66, 3 (2017), 1985–1999. [16] Segata,M.,Bloessl,B.,Joerer,S.,Sommer,C.,Gerla,M.,LoCigno,R.,and Dressler, F. Toward communication strategies for platooning: Simulative and experimental evaluation. IEEE Trans. Veh. Technol. 64, 12 (2015), 5411–5423. [17] Sommer, C., German, R., and Dressler, F. Bidirectionally coupled network and road traffic simulation for improved IVC analysis. IEEE Trans. Mobile Comput. 10, 1 (2011), 3–15. [18] Sutton, R. S., and Barto, A. G. Introduction to Reinforcement Learning, 2nd ed. MIT Press, Cambridge, MA, USA, 2020. [19] Teixeira, F. A., e Silva, V. F., Leoni, J. L., Macedo, D. F., and Nogueira, J. M. Vehicular networks using the IEEE 802.11p standard: An experimental analysis. Vehicular Commun. 1, 2 (2014), 91–96. [20] Velasqez, K., Abreu, D., Curado, M., and Monteiro, E. Service placement for latency reduction in the internet of things. Proc. IEEE 72, 2 (2017), 105–115. [21] Virdis, A., Nardini, G., and Stea, G. A framework for MEC-enabled platooning. In Proc. IEEE WCNCW (2019), pp. 1–6. [22] Watkins, C. J. C. H. Learning from Delayed Rewards. PhD thesis, King’s College, Cambridge, UK, May 1989. [23] Öncü, S., Ploeg, J., van de Wouw, N., and Nijmeijer, H. Cooperative adaptive cruise control: Network-aware analysis of string stability. IEEE Trans. Intell. Transp. Syst. 15, 4 (2014), 1527–1537. | es |