The increasing usage of IoT devices has generated an extensive volume of data which resulted in the establishment of data centers with well-structured computing infrastructure. Reducing underutilized resources of such data centers can be achieved by monitoring the tasks and offloading them across various compute units. This approach can also be used in mini mobile data ponds generated by edge devices and smart vehicles. This research aims to improve and utilize the usage of computing resources in distributed edge devices by forming a dynamic mesh network. The nodes in the mesh network shall share their computing tasks with another node that possesses unused computing resources. This proposed method ensures the minimization of data transfer between entities. The proposed AirDnD vision will be applied to a practical scenario relevant to an autonomous vehicle that approaches an intersection commonly known as ``looking around the corner'' in related literature, collecting essential computational results from nearby vehicles to enhance its perception. The proposed solution consists of three models that transform growing amounts of geographically distributed edge devices into a living organism.

翻译：物联网设备日益广泛的使用产生了海量数据，进而催生了具备完善计算基础设施的数据中心。通过监控任务并将其卸载到不同的计算单元，可以减少此类数据中心中未充分利用的资源。这种方法同样适用于由边缘设备和智能车辆产生的微型移动数据池。本研究旨在通过构建动态网状网络，以改进和利用分布式边缘设备中的计算资源。网状网络中的节点将把其计算任务共享给另一个拥有闲置计算资源的节点。所提出的方法确保了实体间数据传输的最小化。拟议的AirDnD愿景将应用于一个与自动驾驶车辆相关的实际场景，即车辆接近交叉路口时（相关文献中通常称为“环顾转角”），通过从邻近车辆收集关键计算结果以增强其感知能力。该解决方案包含三个模型，可将日益增长的地理分布式边缘设备转变为一个有机生命体。