TY  - EJOU
AU  - Chen, Ting 
AU  - Wang, Shujiao 
AU  - Fan, Xin 
AU  - Zhang, Xiujuan 
AU  - Luo, Chuanwen 
AU  - Hong, Yi 

TI  - UAV-Assisted Multi-Object Computing Offloading for Blockchain-Enabled Vehicle-to-Everything Systems
T2  - Computers, Materials \& Continua

PY  - 2024
VL  - 81
IS  - 3
SN  - 1546-2226

AB  - This paper investigates an unmanned aerial vehicle (UAV)-assisted multi-object offloading scheme for blockchain-enabled Vehicle-to-Everything (V2X) systems. Due to the presence of an eavesdropper (Eve), the system’s communication links may be insecure. This paper proposes deploying an intelligent reflecting surface (IRS) on the UAV to enhance the communication performance of mobile vehicles, improve system flexibility, and alleviate eavesdropping on communication links. The links for uploading task data from vehicles to a base station (BS) are protected by IRS-assisted physical layer security (PLS). Upon receiving task data, the computing resources provided by the edge computing servers (MEC) are allocated to vehicles for task execution. Existing blockchain-based computation offloading schemes typically focus on improving network performance, such as minimizing energy consumption or latency, while neglecting the Gas fees for computation offloading and the costs required for MEC computation, leading to an imbalance between service fees and resource allocation. This paper uses a utility-oriented computation offloading scheme to balance costs and resources. This paper proposes alternating phase optimization and power optimization to optimize the energy consumption, latency, and communication secrecy rate, thereby maximizing the weighted total utility of the system. Simulation results demonstrate a notable enhancement in the weighted total system utility and resource utilization, thereby corroborating the viability of our approach for practical applications.
KW  - UAV; intelligent reflecting surface; vehicle to everything; task offloading; phase shift optimization

DO  - 10.32604/cmc.2024.056961