VR Service Delay Guarantee with Interest Prediction: A Joint Caching, Computing and Communication Optimization Approach

This paper investigates the Virtual Reality (VR) service delay performance for an edge-terminal cooperative system. A convolutional neural network (CNN)-based user interest analysis method is first proposed to characterize the content requesting behavior. Based on this, a service delay minimization problem is formulated with consideration of performance fairness among users. Thereafter, the caching and computing scheme is derived for each user with given communication resources, while a bisection-based communication resource allocation scheme is derived with given content caching and offloading information. With alternative optimization, a joint caching, computing and communication scheme is proposed. The effectiveness of the proposed scheme is finally validated by simulation results.