A survey on intelligent computation offloading and pricing strategy in UAV-Enabled MEC network: Challenges and research directions

The lack of resource constraints for edge servers makes it difficult to simultaneously perform a large number of Mobile Devices’ (MDs) requests. The Mobile Network Operator (MNO) must then select how to delegate MD queries to its Mobile Edge Computing (MEC) server in order to maximize the overall benefit of admitted requests with varying latency needs. Unmanned Aerial Vehicles (UAVs) and Artificial Intelligent (AI) can increase MNO performance because of their flexibility in deployment, high mobility of UAV, and efficiency of AI algorithms. There is a trade-off between the cost incurred by the MD and the profit received by the MNO. Intelligent computing offloading to UAV-enabled MEC, on the other hand, is a promising way to bridge the gap between MDs' limited processing resources, as well as the intelligent algorithms that are utilized for computation offloading in the UAV-MEC network and the high computing demands of upcoming applications. This study looks at some of the research on the benefits of computation offloading process in the UAV-MEC network, as well as the intelligent models that are utilized for computation offloading in the UAV-MEC network. In addition, this article examines several intelligent pricing techniques in different structures in the UAV-MEC network. Finally, this work highlights some important open research issues and future research directions of Artificial Intelligent (AI) in computation offloading and applying intelligent pricing strategies in the UAV-MEC network

UAV mobility model for dynamic UAV-to-car communications

0info:eu-repo/semantics/publishe

UAV Mobility model for dynamic UAV-to-car communications in 3D environments

[EN] In scenarios where there is a lack of reliable infrastructures to support car-to-car communications, Unmanned Aerial Vehicles (UAVs) can be deployed as mobile infrastructures. However, the UAVs should be deployed at adequate location and heights to maintain the coverage throughout time as the irregularities of the terrain may have a significant impact on the radio signals sent to distribute information. So, flight altitude and location should be constantly adjusted in order to avoid hilly or mountainous terrains that might hinder the Line-of-Sight (LOS). In this paper, we propose a three-dimensional mobility model to define the movement of the UAV so as to maintain good coverage levels in terms of communications with moving ground vehicles by taking into account the elevation information of the Earth's surface and the signal power towards the different vehicles. 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