Abstract

Virtual reality (VR) video services are becoming increasingly popular in Internet of Things (IoT) owing to its immersive experience. The realization of immersive experience relies on extremely large amount of data transmitted, restricting its application. To meet the transmission requirement of VR video services, this paper designs a user-centric network based on the mobile edge computing (MEC) framework, where the 2D/3D field of view (FOV) files can be cached and the projection process from 2D FOV to 3D FOV can be computed at the VR device or MEC servers collaboratively. Based on this, a cooperative caching and computing-offloading strategy is formulated as a decision matrix, and its optimal closed-form expression is obtained by minimizing the transmission requirement under the strict service time constraint to realize the trade-off between communication, caching and computing (3C trade-off). Besides, the effect of the transmission requirement on the network density is also analyzed to provide useful guidelines for network design. Simulation results demonstrate that the proposed method can achieve quasi-optimal performance compared with other contrasting schemes.

Highlights

  • Due to the immersive experience and full fidelity for user’s perception, wireless virtual reality (VR) emerging as an important application of future Internet of Things (IoT) has attracted more and more attentions [1]

  • In this paper, a user-centric network based on the mobile edge computing (MEC) framework was proposed to meet the transmission requirement of VR video services

  • The 2D and 3D field of view (FOV) files could be collaboratively cached while the projection process from 2D FOV to 3D FOV could be computed at the VR device or MEC servers

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Summary

INTRODUCTION

Due to the immersive experience and full fidelity for user’s perception, wireless virtual reality (VR) emerging as an important application of future Internet of Things (IoT) has attracted more and more attentions [1]. The immersive experience of VR video mainly depends on the delivery of massive amount of data (in Gigabyte) within an ultra-low latency, in generally, 20 ms It requires an ultra-high transmission rate, resulting in a significant burden on the wireless backhaul link [3]. The typical paradigm of mobile edge computing (MEC) is envisioned as one of the key enablers for VR video services, which combines wireless transmission network and computing-caching capabilities at edge network (including MEC server and VR device) [5]–[7]. The network allows the FOV files to be cached and the projection process to be computed at the VR device or MEC servers collaboratively, thereby obtaining the collaborative gain and significantly reducing the transmission requirement under the strict service time constraint of VR videos.

RELATED WORK
USER-CENTRIC NETWORK ARCHITECTURE
COOPERATIVE CACHING AND
SERVICE MECHANISM AND ANALYSIS
PROBLEM FORMULATION
DECISION PROPERTY ANALYSIS AND OPTIMAL
3: For any viewpoint m
PERFORMANCE EVALUATION
SIMULATION RESULTS AND DISCUSSIONS
Findings
CONCLUSION
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