Task scheduling optimization strategy for roadside unit based on security strength

In the context of cooperative vehicle-infrastructure systems (CVIS), vehicles often offload computational tasks to roadside units (RSUs) for execution due to their own constrained computing resources. A novel approach that has garnered increased attention involves the "vehicle-edge-cloud" framework, wherein RSUs decide whether to process tasks locally or to offload them to the cloud. The open and unpredictable nature of the wireless channels on the "edge-cloud" interface necessitates the incorporation of a security mechanism to safeguard the integrity of information transmission. However, integrating such a security mechanism can escalate the energy consumption of RSUs. Addressing the challenge of jointly optimizing roadside energy consumption and information security utility, without compromising task delay constraints, is a complex issue. To tackle this, an energy-packets queue tradeoff of task scheme and encryption strategy (EPTS) was introduced. This approach involved the development of a vehicle speed state model, a task encryption model, a data cache queue model, and a task calculation model, along with the formulation of an optimization objective function. The optimization model was subsequently transformed using Lyapunov optimization theory and was reformulated as a knapsack problem for resolution. The simulation results confirm the EPTS's commendable convergence and effectiveness. The average objective value achieved by the proposed EPTS was found to be 17% superior to that of the Equal Allocation Strategy (EAS) and 21% superior to the queue-weighted strategy (QS).