科研成果详情

Recently, the vehicle-to-everything (V2X) paradigm is attracting more attention from both academia and industry. In the smart city, there are a huge number of roadside smart devices (RSDs) undertaking various sensing and monitoring tasks, and they collect information among V2X devices for various applications. With the software-defined technology applying into RSDs, one of the challenging issues is how to update the software of RSDs in a fast and low-cost way. We argue that recruiting a large number of vehicles to disseminate the update code for such RSDs through vehicle-to-sensing devices communications technology is an effective method. A cost-efficient greedy code mules selection scheme (CGCSS) is proposed to disseminate code to a huge number of RSDs in the smart city. In CGCSS, a task is defined as the process of transmitting the update code from the mobile code station (MCS) to RSD. So, the goal of CGCSS is to recruit an appropriate number of vehicles to finish the tasks with low cost and high coverage. A measure function is proposed to take the historical trajectories and cost into account. Therefore, the vehicles with high task completion possibility and low price will be selected as code mules (CMs). Then, a high-performance MCS deploy scheme (HMDS) is proposed to select the optimized MCS positions according to the movement and frequency of the CMs to optimize the performance of the system. Finally, extensive experiments using the real trajectory dataset have been done. The results show the better performance of CGCSS than the basic greedy code mule select scheme and the random code mules select scheme in terms of completion rate, average price, and cost-performance ratio, and the results confirm the validity of the proposed HMDS as well.