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在集成动脉/Simu5G仿真框架中实现移动边缘计算辅助的集体感知

Implementation of MEC-Assisted Collective Perception in an Integrated Artery/Simu5G Simulation Framework.

作者信息

Kovács Gergely Attila, Bokor László

机构信息

Department of Networked Systems and Services, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Műegyetem rkp. 3., H-1111 Budapest, Hungary.

ELKH-BME Cloud Applications Research Group, Magyar Tudósok Körútja 2, H-1117 Budapest, Hungary.

出版信息

Sensors (Basel). 2023 Sep 19;23(18):7968. doi: 10.3390/s23187968.

Abstract

Advanced vehicle-to-everything (V2X) safety applications must operate with ultra-low latency and be highly reliable. Therefore, they require sophisticated supporting technologies. This is especially true for cooperative applications, such as Collective Perception (CP), where a large amount of data constantly flows among vehicles and between vehicles and a network intelligence server. Both low and high-level support is needed for such an operation, meaning that various access technologies and other architectural elements also need to incorporate features enabling the effective use of V2X applications with strict requirements. The new 5G core architecture promises even more supporting technologies, like Multi-access Edge Computing (MEC). To test the performance of these technologies, an integrated framework for V2X simulations with 5G network elements is proposed in the form of combining Simu5G, a standalone 5G implementation, with the go-to V2X-simulator, Artery. As a first step toward a fully functional MEC-assisted CP Service, an extension to Simu5G's edge implementation is introduced. The edge application is responsible for dispatching the Collective Perception Messages generated by the vehicles via the 5G connectivity so that a MEC server provided by the network can process incoming data. Simulation results prove the operability of the proposed integrated system and edge computing's potential in assisting V2X scenarios.

摘要

先进的车与万物(V2X)安全应用必须以超低延迟运行且高度可靠。因此,它们需要复杂的支持技术。对于协作应用来说尤其如此,比如集体感知(CP),在这种应用中,大量数据在车辆之间以及车辆与网络智能服务器之间持续流动。这种操作既需要底层支持也需要高层支持,这意味着各种接入技术和其他架构元素也需要纳入一些功能,以便能有效使用有严格要求的V2X应用。新的5G核心架构有望提供更多支持技术,如多接入边缘计算(MEC)。为了测试这些技术的性能,提出了一个用于V2X仿真的集成框架,该框架将独立的5G实现方案Simu5G与常用的V2X模拟器Artery相结合,用于模拟5G网络元素。作为迈向功能完备的MEC辅助CP服务的第一步,引入了对Simu5G边缘实现的扩展。边缘应用负责通过5G连接调度车辆生成的集体感知消息,以便网络提供的MEC服务器能够处理传入数据。仿真结果证明了所提出的集成系统的可操作性以及边缘计算在辅助V2X场景方面的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67ad/10534514/94b6e7e0cff5/sensors-23-07968-g001.jpg

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