车联网基于信任度的RSU识别及资源分配算法

在车联网中，由于部分路侧单元（RSU）的位置比较偏远，无法得到网络管理员的及时维护，可能遭到攻击，变为不可信任的路侧单元，降低了车辆的通信质量和网络能效.为了有效地识别RSU的可靠性，提出了一种基于信任度的路侧单元识别及资源分配算法，将路侧单元识别、传输模式的选择和功率分配联合建模为网络能效的优化问题，并分成3个子优化问题，分别求解.首先，采用基于信任度的RSU识别算法，识别出可信任和不可信任的路侧单元；其次，优化车辆资源块配置和链路选择；最后，通过次梯度算法优化传输功率，最大化网络能效.理论分析和仿真结果表明，所提算法具备较低的复杂度，可以达到较高的路侧单元识别准确度，并有效地提升网络总能效.

Trust Degree Based RSU Recognition and Resource Allocation in Vehicular Networks

In network of vehicles, due to some roadside units (RSU) are remote and cannot be maintained timely by network administrator, they may be attacked and become untrustworthy RSUs, resulting in reduction of vehicle communication quality and network energy efficiency. To effectively identify the reliability of the RSU, a trust degree-based RSU recognition and resource allocation algorithm (TRRA) is proposed. In this algorithm, roadside unit identification, transmission mode selection, and power allocation are jointly modeled as the network energy efficiency optimization problem, which is divided into three sub-optimization problems to solve respectively. Firstly, the trust degree-based RSU recognition algorithm is used to identify the trusted and untrusted roadside units; Secondly, the resource block allocation and the link selection are optimized; Finally, the sub-gradient algorithm is used to optimize the transmission power and maximize the network energy efficiency. Simulations show that the proposed algorithm has lower complexity, which can achieve higher recognition accuracy of roadside units, and effectively improve the overall network energy efficiency.