Abstract
The video traffic offloading in edge networks is an effective method for remission of congestion of backward paths in 5G networks by continual optimization of video distribution to promote scale and efficiency of video delivery in edge networks (e.g., D2D-based near-end sharing). Because the video resources are dispersedly cached in local buffer of mobile devices of video users, the management of local video resources of video users in edge networks (e.g., caching and removing of local videos) causes dynamic variation of video distribution in networks. The real-time adjustment of local resources of users in terms of the influence levels (e.g., promotion and recession) of video sharing performance is significant for the continual distribution optimization. In this paper, we propose a novel Social-aware Edge Caching Strategy of Video Resources in 5G Ultra-Dense Network (SECS). SECS designs an estimation method of interest domain of users, which employs the Spectral Clustering to generate initial video clusters and makes use of the Fuzzy C-Means (FCM) to refine the initial video clusters. A user clustering method is proposed, which enables the users with common and similar interests to be clustered into the same groups by estimating similarity levels of interest domain between users. SECS designs a performance-aware video caching strategy, which enables the users intelligently implement management (caching and removing) of local video resources in terms of influence for the intragroup sharing performance. Extensive tests show how SECS achieves much better performance results in comparison with the state-of-the-art solutions.
Highlights
We propose a novel Social-aware Edge Caching Strategy of Video Resources in 5G Ultra-Dense Network (SECS)
The backhaul paths in the 5G networks inevitably are subjected by the network congestion because of dense access. e high startup delay and unbearable packet loss caused by the network congestion lead to unsmooth playback and video picture distortion, which brings severe negative influence for user quality of experience (QoE). erefore, offloading video traffic in edge networks without intervention of 5G nodes is significant for relieving congestion levels of backhaul networks
Zhang et al propose a delay-optimal cooperative edge caching in wireless networks, which can optimize content placement and cluster size according to stochastic information of comprehensive measurement of network topology, traffic distribution, channel quality and file popularity [25]. e authors proposes a greedy content placement algorithm using bandwidth allocation optimization and a condition constraining the maximal cluster size based on tradeoff between caching diversity and spectrum efficiency
Summary
Shijie Jia ,1 Zhen Zhou ,1 WeiLing Li ,1 Youzhong Ma ,1 Ruiling Zhang ,1 and Tianyin Wang 2,3. E real-time adjustment of local resources of users in terms of the influence levels (e.g., promotion and recession) of video sharing performance is significant for the continual distribution optimization. We propose a novel Social-aware Edge Caching Strategy of Video Resources in 5G Ultra-Dense Network (SECS). SECS designs a performance-aware video caching strategy, which enables the users intelligently implement management (caching and removing) of local video resources in terms of influence for the intragroup sharing performance. The 5G makes use of the ultra-dense deployment to promote network coverage and access capability, which supports more video users to ubiquitously fetch video content via the 5G networks. E high startup delay and unbearable packet loss caused by the network congestion lead to unsmooth playback and video picture distortion, which brings severe negative influence for user quality of experience (QoE). The backhaul paths in the 5G networks inevitably are subjected by the network congestion because of dense access. e high startup delay and unbearable packet loss caused by the network congestion lead to unsmooth playback and video picture distortion, which brings severe negative influence for user quality of experience (QoE). erefore, offloading video traffic in edge networks without intervention of 5G nodes is significant for relieving congestion levels of backhaul networks
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