Energy Optimization in Dual-RIS UAV-Aided MEC-Enabled Internet of Vehicles

Sensors

Angelos Michalas¹  Emmanouel T. Michailidis²  Nikolaos I. Miridakis³  Emmanouil Skondras⁴  Dimitrios J. Vergados⁵ 

[1] Department of Electrical and Computer Engineering, University of Western Macedonia, Karamanli & Ligeris, 50131 Kozani, Greece;Department of Electrical and Electronics Engineering, University of West Attica, Ancient Olive Grove Campus, 250 Thivon & P. Ralli Str, 12241 Egaleo, Greece;Department of Informatics and Computer Engineering, University of West Attica, Egaleo Park Campus, Ag. Spyridonos Str, 12243 Egaleo, Greece;Department of Informatics, University of Piraeus, 80 Karaoli & Dimitriou St., 18534 Piraeus, Greece;Department of Informatics, University of Western Macedonia, Fourka Area, 52100 Kastoria, Greece;

关键词: computation offloading;    energy efficiency;    Internet of Vehicles (IoV);    mobile edge computing (MEC);    reconfigurable intelligent surface (RIS);    unmanned aerial vehicle (UAV);   

DOI  :  10.3390/s21134392

来源: DOAJ

【 摘 要 】

Mobile edge computing (MEC) represents an enabling technology for prospective Internet of Vehicles (IoV) networks. However, the complex vehicular propagation environment may hinder computation offloading. To this end, this paper proposes a novel computation offloading framework for IoV and presents an unmanned aerial vehicle (UAV)-aided network architecture. It is considered that the connected vehicles in a IoV ecosystem should fully offload latency-critical computation-intensive tasks to road side units (RSUs) that integrate MEC functionalities. In this regard, a UAV is deployed to serve as an aerial RSU (ARSU) and also operate as an aerial relay to offload part of the tasks to a ground RSU (GRSU). In order to further enhance the end-to-end communication during data offloading, the proposed architecture relies on reconfigurable intelligent surface (RIS) units consisting of arrays of reflecting elements. In particular, a dual-RIS configuration is presented, where each RIS unit serves its nearby network nodes. Since perfect phase estimation or high-precision configuration of the reflection phases is impractical in highly mobile IoV environments, data offloading via RIS units with phase errors is considered. As the efficient energy management of resource-constrained electric vehicles and battery-enabled RSUs is of outmost importance, this paper proposes an optimization approach that intends to minimize the weighted total energy consumption (WTEC) of the vehicles and ARSU subject to transmit power constraints, timeslot scheduling, and task allocation. Extensive numerical calculations are carried out to verify the efficacy of the optimized dual-RIS-assisted wireless transmission.

【 授权许可】

Unknown