Efficient Multi-View 3D Video Multicast with Mobile Edge Computing
Jian-Jhih Kuo, De-Nian Yang, Weicheng Li, Wen-Tsuen Chen · 2018
With the emergence of multi-view 3D videos, network operators now face a new challenge to resolve the dramatic increase of the network bandwidth required to support all subscribed views (typically 16 or 32) of a video. Recently, Depth-Image-Based Rendering (DIBR) in Computer Vision has been demonstrated as a promising way for efficient multi-view 3D video multicast, because many views can be synthesized in mobile devices and no longer need to be transmitted. Nevertheless, DIBR is computationally intensive and incurs additional power consumption in mobile devices, and unsubscribed views need to be transmitted to mobile users for DIBR. In this paper, therefore, we aim to leverage Mobile Edge Computing (MEC) for DIBR to foster effective and efficient multi-view video multicast. We formulate a new problem, named Multi-view Multicast Synthesis and Delivery (MMSD) and prove the NP-Hardness. We design an approximation algorithm, named Merge Search Forest Algorithm (MSFA), to choose the view to be synthesized and build a multicast topology including a low-cost forest for supporting each subscribed view. Simulation results manifest that MSFA outperforms the existing approaches by 30% to 50% of the total communication and computation cost.