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.

中文翻译：

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一种用于车载边缘多接入网络中计算卸载的高效的面向移动性的检索协议

随着具有高计算和低延迟需求的移动和车载应用的出现，例如智能交通系统和基于物联网的应用，车载边缘计算 (VEC) 架构的计算卸载越来越受到关注。然而，要有效地使用 VEC 的资源，需要解决现有的挑战。根本性的挑战来自车辆的高机动性和间歇性或缺乏连通性。在本文中，我们对 VEC 中的计算卸载任务进行建模，目的是评估模拟有助于提高 VEC 性能的元素的能力。此外，我们提出了移动性预测检索（MPR）数据检索协议，这允许 VEC 通过使用车辆和路边单元作为通信节点来有效地检索卸载应用程序的输出处理数据。开发的协议使用网络基础设施和用户的地理位置信息在车辆边缘计算环境中完成有效的数据检索。最后，所进行的实验表明，与相关技术相比，所提出的协议以更低的通信延迟实现了更可靠的数据检索。