Online 6-DoF view touring has become increasingly popular due to hardware advances and the recent pandemic. One way for content creators to support many 6-DoF clients is by transmitting 3D content to them, which leads to content leakage. Another way for content creators is to render and stream novel views for 6-DoF clients, which incurs staggering computational and networking workloads. In this paper, we develop a blind streaming system that leverages cloud service providers between content creators and 6-DoF clients. Our system has two core design objectives: (i) to generate high-quality novel views for 6-DoF clients without retrieving 3D content from content creators, (ii) to support many 6-DoF clients without overloading the content creators. We achieve these two goals in the following steps. First, we design a source view request/response interface between cloud service providers and content creators for efficient communications. Second, we design novel view optimization algorithms for cloud service providers to intelligently select the minimal set of source views while considering the workload of content creators. Third, we employ scalable client side view synthesis for 6-DoF clients with heterogeneous device capabilities and personalized 6-DoF client poses and preferences. Our evaluation results demonstrate the merits of our solution, compared to the state-of-the-arts, our system: (i) improves synthesized novel views by 2.27 dB in PSNR and 12 in VMAF on average and (ii) reduces the bandwidth consumption by 94% on average. In fact, our solution approaches the performance of an unrealistic optimal solution with unlimited source views, achieving performance gaps as small as 0.75 dB in PSNR and 3.8 in VMAF.

We develop, implement, and demonstrate an open-source simulator, called AirSimN, for evaluating drone-based wireless networks in this extended abstract. AirSimN is different from all prior attempts in the literature because it concurrently supports aerodynamic, computer vision, and network simulations. We carefully design it to minimize the effort of realizing virtually arbitrary drone applications, thanks to the active and popular AirSim and NS-3 projects. Many mobile computing and wireless networking projects on, e.g., drone feedback controllers, drone vision algorithms, and 5G/6G cellular network planning, can leverage AirSimN for large-scale evaluations.