Multi-layer Video Streaming with Helper Nodes Using Network Coding

Abstract

Abstract-Video streaming is one of the dominant forms of traffic on the Internet. This increases workload on the video servers, which leads to substantial slowdowns. In order to resolve the slowdown problem, and to provide a scalable and robust infrastructure to support on-demand streaming, helper-assisted video-on-demand (VoD) systems have been introduced. In this architecture, helper nodes, which are micro-servers with limited storage and bandwidth resources, download and store the userrequested videos from a central server to decrease the load on the central server. Multi-layer videos, in which a video is divided into different layers, can also be used to improve scalability. In this paper, we study the problem of utilizing the helper nodes to minimize the pressure on the central servers. We formulate the problem as a linear programming (LP) optimization using joint inter-and intra-layer network coding (NC). We show that a lightweight triangular inter-layer NC can be used, instead of the general form of inter-layer NC, to achieve the optimal solution. Our solution can also be implemented in a distributed manner. We show how our method can be extended to the case of wireless live streaming, in which a set of videos is broadcast. We carefully study the convergence and the gain of our distributed approach.

Scalable Video Streaming With Helper Nodes Using Random Linear Network Coding

“…By random topologies we mean randomly connecting the users to the helpers and randomly setting the bandwidth limit of the helpers. Number of adjacent helpers to user is randomly selected in the range of [1,3]. Assuming that this number is , we connect user to helpers.…”

“…11(a), we compare the loads on the central server. Each video contains 5 layers, and the number of requested layers by each user is randomly chosen in the range of [1,5]. The other parameters are shown in Table II.…”

“…14(a) shows the load on the server of the different methods. In this figure, the video rates, video sizes, storage capacity, and bandwidth capacity of the helpers are in the range of [1,2], [0.5, 2], [0. 5,2], and [1,3], respectively.…”

“…The helpers' bandwidths are in the range of [5,10], and the video size, video rate, and the storage capacities are set to 4, 4, and 1. Also, the degree of each user is in the range of [1,4], and we set the number of requested layers of each user to its degree. Fig.…”

“…18. For this purpose, we add 5 users at both iterations 800 and 1600, and we randomly connect them to [1,3] helpers. We also remove 5 users at iteration 2400.…”