An Efficient Mobility-Oriented Retrieval Protocol for Computation Offloading in Vehicular Edge Multi-Access Network

Computation offloading for vehicular edge computing (VEC) architecture has gained increasing attention, with the emergence of mobile and vehicular applications with high-computing and low-latency demands, such as Intelligent Transportation Systems and IoT-based applications. However, existing challenges need to be addressed for VEC's resources to be used in an efficient manner. The fundamental challenges arise from high vehicular mobility and intermittent or lack of connectivity. In this paper, we model the computation offloading task in VEC, with the goal of assessing the ability to simulate the elements that contribute to enhancing its performance in VEC. In addition, we propose the Mobility Prediction Retrieval (MPR) data retrieval protocol, which allows VEC to efficiently retrieve the output processed data of the offloaded application by using both vehicles and road side units as communication nodes. The developed protocol uses geo-location information of the network infrastructure and the users to accomplish an efficient data retrieval in a Vehicular Edge Computing environment. Finally, the experiments performed show that the proposed protocol to achieves a more reliable data retrieval with lower communication delay when compared to related techniques.