Abstract
V2X system support a large number of new services and protocols, therefore, moving to integrated interaction with the surrounding information space, defined as V2X interoperability, should ensure the interoperability of the various networks and systems involved in providing services to users [5]. The data must be transmitted with low latency and high speed between vehicles. This requires the introduction of a new high-speed network, advanced road transport, and telecommunications infrastructure. To ensure the effective functioning of V2X networks, in this paper we propose to use flying fog computing for a reliable and efficient system for simulation model, we used a UAVs as a base station (BS) equipped by a controller (CU) that provide execution of the requests arriving from the users equipment located in the communication range of the BS. Users that are connected with the BS requests flow that arrive at CU, we assume that one cloud server (CS) can serve a number of UAVs. CU is described as a service system which provides execution of some requests simultaneously. We assume that the execution of each request flow from users needs a fixed amount of energy. We’ve noticed that in the case of low traffic intensity the delay value increases with increasing of the part of traffic forwarded to the cloud, the energy consumption lower if the part of redirected traffic is bigger.
This paper has been supported by the RUDN University Strategic Academic Leadership Program.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Rihan, M., Elwekeil, M., Yang, Y., Huang, L., Xu, C., Selim, M.M: Deep-VFog: when artificial intelligence meets fog computing in V2X. IEEE Syst. J. (2020)
Al-Ansi, A., Al-Ansi, A.M., Muthanna, A., Elgendy, I.A., Koucheryavy, A.: Survey on intelligence edge computing in 6G: characteristics, challenges, potential use cases, and market drivers. Future Internet 13(5), 118 (2021)
Artem, V., Al-Sveiti, M., Elgendy, I.A., Kovtunenko, A.S., Muthanna, A.: Detection and recognition of moving biological objects for autonomous vehicles using intelligent edge computing/LoRaWAN mesh system. In: NEW2AN/ruSMART -2020, Part II. LNCS, vol. 12526, pp. 3–15. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-65729-1_1
Ding, G., Wu, Q., Zhang, L., Lin, Y., Tsiftsis, T.A., Yao, Y.-D.: An amateur drone surveillance system based on the cognitive internet of things. IEEE Commun. Mag. 56(1), 29–35 (2018)
Vladyko, A., Khakimov, A., Muthanna, A., Ateya, A.A., Koucheryavy, A.: Distributed edge computing to assist ultra-low-latency VANET applications. Future Internet 11(6), 128 (2019)
Elgendy, I.A., Muthanna, A., Hammoudeh, M., Shaiba, H., Unal, D., Khayyat, M.: Advanced deep learning for resource allocation and security aware data offloading in industrial mobile edge computing. Big Data (2021)
Pinto, M.F., Marcato, A.L., Melo, A.G., Honório, L.M., Urdiales, C.: A framework for analyzing fog-cloud computing cooperation applied to information processing of UAVs. Wireless Communications and Mobile Computing (2019)
Mohamed, N., Al-Jaroodi, J., Jawhar, I., Noura, H., Mahmoud, S.: UAVFog: a UAV-based fog computing for internet of things. In: 2017 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), pp. 1–8. IEEE (2017)
Hou, X., Ren, Z., Wang, J., Zheng, S., Cheng, W., Zhang, H.: Distributed fog computing for latency and reliability guaranteed swarm of drones. IEEE Access 8, 7117–7130 (2020)
Acknowledgment
This paper has been supported by the RUDN University Strategic Academic Leadership Program.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
AlSweity, M., Muthanna, A., Elgendy, I.A., Koucheryavy, A. (2021). Traffic Management Algorithm for V2X-Based Flying Fog System. In: Vishnevskiy, V.M., Samouylov, K.E., Kozyrev, D.V. (eds) Distributed Computer and Communication Networks: Control, Computation, Communications. DCCN 2021. Lecture Notes in Computer Science(), vol 13144. Springer, Cham. https://doi.org/10.1007/978-3-030-92507-9_4
Download citation
DOI: https://doi.org/10.1007/978-3-030-92507-9_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-92506-2
Online ISBN: 978-3-030-92507-9
eBook Packages: Computer ScienceComputer Science (R0)