This paper presents an innovative framework that synergistically enhances computing performance through ubiquitous computing power distribution and dynamic computing node accessibility control via adaptive unmanned aerial vehicle (UAV) positioning, establishing UAV-enabled Computing Power Networks (UAV-CPNs). In UAV-CPNs, UAVs function as dynamic aerial relays, outsourcing tasks generated in the request zone to an expanded service zone, consisting of a diverse range of computing devices, from vehicles with onboard computational capabilities and edge servers to dedicated computing nodes. This approach has the potential to alleviate communication bottlenecks in traditional computing power networks and overcome the "island effect" observed in multi-access edge computing. However, how to quantify the network performance under the complex spatio-temporal dynamics of both communication and computing power is a significant challenge, which introduces intricacies beyond those found in conventional networks. To address this, in this paper, we introduce task completion probability as the primary performance metric for evaluating the ability of UAV-CPNs to complete ground users' tasks within specified end-to-end latency requirements. Utilizing theories from stochastic processes and stochastic geometry, we derive analytical expressions that facilitate the assessment of this metric. Our numerical results emphasize that striking a delicate balance between communication and computational capabilities is essential for enhancing the performance of UAV-CPNs. Moreover, our findings show significant performance gains from the widespread distribution of computing nodes.

翻译：本文提出了一种创新框架，通过泛在计算能力分布与自适应无人机（UAV）定位实现的动态计算节点可访问性控制协同增强计算性能，从而构建无人机赋能的计算能力网络（UAV-CPNs）。在UAV-CPNs中，无人机作为动态空中中继，将请求区域内生成的任务外包至扩展的服务区域，该区域包含多样化的计算设备，从具备车载计算能力的车辆、边缘服务器到专用计算节点。这种方法有望缓解传统计算能力网络中的通信瓶颈，并克服多接入边缘计算中观察到的“孤岛效应”。然而，如何在通信与计算能力复杂的时空动态下量化网络性能是一项重大挑战，其复杂性超越了传统网络。为此，本文引入任务完成概率作为核心性能指标，用于评估UAV-CPNs在指定端到端延迟要求内完成地面用户任务的能力。基于随机过程与随机几何理论，我们推导了便于评估该指标的解析表达式。数值结果表明，通信与计算能力之间的精细平衡对于提升UAV-CPNs性能至关重要。此外，研究发现计算节点的广泛分布可带来显著的性能增益。