Abstract

In this paper, we design a computing, communication and caching scheme for edge caching-based video streaming in order to improve the network performance. Firstly, we optimize the system's energy efficiency and delay with the aid of network function virtualization. Then, a dynamic edge caching decision is developed, and based on Lyapunov optimization, an alternating resource optimization algorithm is proposed for allocating the optimal subcarrier and power resources, video caching and computing resources. Our numerical results show that the proposed scheme outperforms both the traditional caching scheme as well as the least frequently used (LFU)-40% regime, and strikes a compelling tradeoff between the energy efficiency and delay.

Highlights

  • For high-throughput video streaming, edge caching substantially reduces users’ delay, whilst improving the network performance [1]

  • If the requested contents have been cached without compression, the user is associated with vBS1 directly for video-acquisition; otherwise the user is associated with vBS2 for fetching, transcoding and transmission

  • We compare the performance of our 3C scheme to that of the traditional caching scheme, where the most popular videos are cached at the edge without compression and the remaining videos are transmitted over the backhaul link

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Summary

INTRODUCTION

For high-throughput video streaming, edge caching substantially reduces users’ delay, whilst improving the network performance [1]. Ma et al [4] proposed to exploit both the temporal and spatial video request patterns observed for improving the performance by edge content caching, while Li et al [5] minimized the average video distortion of all users. They all improve the user experience by caching strategies or by optimizing the edge cache size. The compressed video can be transcoded into different-resolution versions required by users on the fly In this way, video compression can alleviate the shortage of edge storage space and congestion of the backhaul link through online transcoding, so as to integrate computing, caching, and communication (3C) resources.

SYSTEM MODEL
Transmission Phase
PROBLEM FORMULATION AND SOLUTION
Communication Subproblem
2: REPEAT 3
Edge Caching Subproblem
NUMERICAL RESULTS AND DISCUSSIONS
CONCLUSIONS
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