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Distributed computing enables Internet of vehicle (IoV) services by collaboratively utilizing the computing resources from the network edge and the vehicles. However, the computing interruption issue caused by frequent edge network handoffs, and a severe shortage of computing resources are two problems in providing IoV services. High altitude platform station (HAPS) computing can be a promising addition to existing distributed computing frameworks because of its wide coverage and strong computational capabilities. In this regard, this paper proposes an adaptive scheme in a new distributed computing framework that involves HAPS computing to deal with the two problems of the IoV. Based on the diverse demands of vehicles, network dynamics, and the time-sensitivity of handoffs, the proposed scheme flexibly divides each task into three parts and assigns them to the vehicle, roadside units (RSUs), and a HAPS to perform synchronous computing. The scheme also constrains the computing of tasks at RSUs such that they are completed before handoffs to avoid the risk of computing interruptions. On this basis, we formulate a delay minimization problem that considers task-splitting ratio, transmit power, bandwidth allocation, and computing resource allocation. To solve the problem, variable replacement and successive convex approximation-based method are proposed. The simulation results show that this scheme not only avoids the negative effects caused by handoffs in a flexible manner, it also takes delay performance into account and maintains the delay stability.Index Terms-Internet of vehicles (IoV), High altitude platform station (HAPS), distributed computing, edge network handoff.

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Owing to a dramatic increase of traffic, high demand for quality of service (QoS), and insufficient radio resources, real-time video streaming transmission with stringent delay constraints has been intensely concerned. By exploiting the device-to-device (D2D) multicast communications, this paper proposes a video streaming transmission scheme based on the frame priority (FP) to improve the QoS perceived by users and the users' satisfaction about the video quality. First, the FP strategy is proposed, which mainly considers the encoding characteristics of video streaming and users' feedback to ensure that the frames to be retransmitted are valuable for decoding. Then, in order to transmit a sufficient number of valuable frames within the delay constraints, the optimization of time consumption of the retransmitted frame is formulated. Based on this, the physical-layer resource allocation in the D2D multicast networks is discussed, where the relay selection, D2D subgroup forming, and channel allocation are jointly investigated with the aid of three-dimensional channel quality matrix. Furthermore, a heuristic algorithm is proposed to obtain a near-optimal performance with low complexity. The simulation results verify the advantages of our proposed transmission scheme in users' video reception quality and the satisfaction of all users. INDEX TERMS D2D multicast, frame priority, resource allocation, real-time video.