Analysis and Optimization of Caching and Multicasting for Multi-Quality Videos in Large-Scale Wireless Networks

Abstract

Efficient dissemination of videos is an important problem for mobile telecom carriers. In this paper, to facilitate massive video dissemination, we study joint caching and multicasting for multi-quality videos encoded using two video encoding techniques, namely scalable video coding (SVC), and HEVC or H.264 as in dynamic adaptive streaming over HTTP (DASH) respectively, in a large-scale wireless network. First, for each type of videos, we propose a random caching and multicasting scheme, carefully reflecting the relationship between layers of an SVC-based video or descriptions of a DASH-based video.Then, for each type of videos, we derive tractable expressions for the successful transmission probability in the general and high user density regions, respectively, utilizing tools from stochastic geometry. The analytical results reveal that in the high user density region, the marginal increase of the successful transmission probability with respect to the caching probability of a video with a certain quality reduces when the caching probability increases. Next, for each type of videos, we consider the maximization of the successful transmission probability in the high user density region, which is a convex problem with an exceedingly large number of optimization variables. We propose a two-stage optimization method to obtain a low-complexity near optimal solution by solving a relaxed convex problem and a related packing problem. The optimization results reveal the impact of the caching gain of a layer for an SVCbased video or a description for a DASH-based video on its caching probability. Finally, we show that the proposed solutions for SVC-based and DASH-based videos achieve significant performance gains over baseline schemes in the general and high user density regions, and demonstrate their respective operating regions, using numerical results based on real video sequences. Index TermsCache, multicast, multi-quality video, scalable video coding, dynamic adaptive streaming over HTTP, stochastic geometry, optimization.

QoE-Aware Video Delivery in Multimedia IoT Network with Multiple Eavesdroppers

“…Due to the increasingly personalized user demands and the complexity of the network environment, SVC technology is usually applied to meet the diverse requirements of video delivery in IoT network. In [34], the author used the stochastic geometry tool to increase the probability of successful transmission of multiquality video and proposed a two-stage transmission optimization algorithm based on the convex optimization and the packing problem. In [35], a matching sensing scheme considering relay selection was proposed to optimize the cooperative transmission performance of SVC video and improve the QoE of users.…”

“…In [23], cache-assisted data rate (CADR) was proposed as a performance index to measure the SVC video transmission performance in nonorthogonal channel D2D scene, and a two-stage joint optimization scheme is proposed. However, [34][35][36][37] mainly discussed the perspective of multiquality video transmission, but the cost of cache location and transmission interference in the case of multigroup multicast has not been considered. e D2D auxiliary transmission strategy proposed by [23] is difficult to apply directly in multicast transmission based on multi-SBS.…”

Scalable Video Caching for Information Centric Wireless Networks

“…For improving successful transmission probability, the authors in [14] investigate a layer placement scheme for SVC videos, where multiple video layers are stored in the cache devices of small-cell base stations (SBSs). In [15], caching strategies in large-scale wireless networks are analyzed and optimized, which reveals the relationship between layers of SVC-based videos. Moreover, some recent studies address the transmission latency in SVC-based video caching.…”

“…Update the values of items in O for knapsack k. Layered video contents can be cached in both the edge controller and an AP simultaneously. According to (15), the value of an item D m kvl may vary when the item is put into different knapsacks. Specifically, the value of an item in the edge controller depends on whether it has been cached in APs.…”

Performance analysis of the collaborative caching strategy in an UAV-RAN

“…In this regard, in order to effectively alleviate the serious traffic burden and reduce the transmission delay, wireless caching is proposed, i.e., popular video data is prefetched at the network edges during the off-peak times, which is more attractive for the future communication networks [2][3][4][5][6][7][8]. Combining distributed networks [9][10][11] with the video coding technology, the edge caching networks can provide users with different video viewing experiences [12][13][14][15].…”