Placement of edge servers is the prerequisite of provisioning edge computing services for Internet of Vehicles (IoV). Fixed-site edge servers at Road Side Units (RSUs) or base stations are able to offer basic service coverage for end users, i.e., vehicles on road. However, the server locations and capacity are fixed after deployment, rendering their inefficiency in handling spationtemporal user dynamics. Mobile servers such as buses, on the other hand, have the potential of adding computation elasticity to such system. To this end, this paper studies the feasibility of bus-mounted edge servers based on real traces. First, we investigate the coverage of the buses and base stations using the Shanghai bus/taxi/Telecom datasets, which shows a great potential of bus-based edge servers as they cover a great portion of geographic area and demand points. Next, we build a mathematical model and design a simple greedy heuristic algorithm to select a limited number of buses that maximizes the coverage of demand points, i.e., with a limited purchase budget. We perform trace-driven simulations to verify the performance of the proposed bus selection algorithm. The results show that our approach effectively handles the dynamic user demand under realistic constraints such as server capacity and purchase quantity. Thus, we claim: bus-mounted edge servers for vehicular networks in urban areas are feasible, beneficial, and valuable.
翻译:边缘服务器的部署是为车联网提供边缘计算服务的前提。部署在路侧单元或基站的固定站点边缘服务器能够为终端用户(即道路上的车辆)提供基本的服务覆盖。然而,服务器位置和容量在部署后即固定不变,导致其在处理时空用户动态变化时效率低下。另一方面,公交车等移动服务器则具备为系统增加计算弹性的潜力。为此,本文基于真实轨迹数据研究了车载边缘服务器的可行性。首先,我们利用上海公交车/出租车/电信数据集分析了公交车与基站的覆盖情况,结果显示基于公交车的边缘服务器具有巨大潜力,因其覆盖了大部分地理区域和需求点。接着,我们构建数学模型并设计了一种简单的贪心启发式算法,以在有限的采购预算下选择最优数量的公交车,最大化需求点的覆盖范围。通过基于轨迹的仿真验证了所提公交车选择算法的性能。结果表明,在服务器容量和采购数量等现实约束条件下,我们的方法能有效处理动态用户需求。因此,我们提出:城市区域车联网中采用车载边缘服务器具有可行性、效益性和重要价值。