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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).

In the cooperative vehicle‐infrastructure system (CVIS), due to its computation limitation, vehicles are difficult to handle computing‐intensive delay‐sensitive tasks, so offload tasks to roadside unit (RSU) become popular. Due to the complexity of vehicles' tasks and tasks generated by different vehicles have different delay constraints, minimize energy consumption of RSUs under task dependence and delay constraints is challenging. This paper defines the task priority queuing criterion for the task priority division problem, proposes a task scheduling strategy for energy‐packet queue length tradeoff (TSET) in CVIS under RSUs distributed task scheduling problem and establishes the vehicle speed state model, task model, data queue model, task computing model and energy consumption model. After Lyapunov optimization theory transformed the optimization model, a knapsack problem was described. The simulation results verify that TSET reduces the average energy consumption of roadside units and ensures the stability of the data queue under task dependence and deadline conditions. [ABSTRACT FROM AUTHOR]

In Cooperative Vehicle Infrastructure System (CVIS), the roadside unit (RSU) obtains many kinds of monitoring data through observation equipment carried by the RSU. The monitoring data from RSUs are transmitted to an RSU that is connected to the backbone network using the "store–carry–forward" scheme through the mobile vehicle. The monitoring data obtained by RSUs are timely, and different types of monitoring data have corresponding timelines. Reducing end-to-end delays to ensure more packets can be transmitted before deadlines is challenging. In this paper, we propose a Distributed Packet Scheduling Scheme for Delay-Packets Queue Length Tradeoff System (DDPS) in CVIS to solve the multi-RSU-distributed packet transmission problem. We also establish the vehicle speed state, vehicle communication quantity prediction, data arrival, and end-to-end delay minimization models. After Lyapunov's optimization theory transformed the optimization model, a knapsack problem was described. The simulation results verified that DDPS reduced the end-to-end average delay and ensured the data queue's stability under packet deadline conditions. [ABSTRACT FROM AUTHOR]