Achieving Multi-Attribute Superiority and Sybil Attack Detection in IoV: A Heuristic-Based Dynamic RSU Deployment Scheme

Roadside units (RSUs) play a vital role in intelligent transportation systems (ITS), working as critical elements in delivering superior Internet of Vehicles (IoV) services. A large service coverage and fast accident information diffusion RSU deployment solution can reliably ensure the ITS' quality of service. Simultaneously, with the development of the city and the ITS, changes in traffic flow lead to RSU load imbalance, which will reduce the benefit of the original RSU deployment, and it is necessary to adjust RSU locations with minimal cost. Besides, due to the high visibility of the ITS, RSUs are highly susceptible to external attacks, which is commonly overlooked in existing RSU deployment work. Specifically, Sybil attack is one of the most dangerous attacks against ITS, and it can reshape the network state by forging multiple identities, interfering with risk sensing, etc. Motivated by these, we respectively propose the PSO-meme joint heuristic deployment algorithm (PJHDA) and the heuristic RSU multi-objective adaptation adjustment algorithm (HRMA3) to carry out deployment and adaptation adjustment of the city's RSUs, taking into account the constraint of Sybil attack detection. Numerical results demonstrate that the multi-attribute performance of PJHDA is superior to the existing schemes. Compared with benchmark schemes, the HRMA3 excels in achieving advanced service coverage and load balancing while controlling costs, and both proposed schemes exhibit higher Sybil attack detection rate.