Abstract
Recent advances in modern television systems have had profound consequences for the scalability, stability, and quality of transmitted digital data signals. This is of particular significance for peer-to-peer (P2P) video-on-demand (VoD) related platforms, faced with an immediate and growing demand for reliable service delivery. In response to demands for high-quality video, the key objectives in the construction of the proposed framework were user satisfaction with perceived video quality and the effective utilization of available resources on P2P VoD networks. This study developed a peer-based promoter to support online advertising in P2P VoD networks based on an estimation of video distortion prior to the replication of data stream chunks. The proposed technology enables the recovery of lost video using replicated stream chunks in real time. Load balance is achieved by adjusting the replication level of each candidate group according to the degree-of-distortion, thereby enabling a significant reduction in server load and increased scalability in the P2P VoD system. This approach also promotes the use of advertising as an efficient tool for commercial promotion. Results indicate that the proposed system efficiently satisfies the given fault tolerances.
Highlights
Recent advances in online advertising and peer-to-peer (P2P) video-on-demand (VoD) networks, enabling peers to watch or download internet video clips on demand, have created considerable interest in the construction of integrated frameworks
We propose a method of estimating video distortion for data stream-chunk replication in the P2P VoD advertising network
The RR and bottleneckbased replication method (BR) methods enable downloading of video chunks in the packet buffer by online peers, but those replication strategies do not accurately represent current resource conditions in the P2P VoD network
Summary
Recent advances in online advertising and peer-to-peer (P2P) video-on-demand (VoD) networks, enabling peers to watch or download internet video clips on demand, have created considerable interest in the construction of integrated frameworks. The proposed approach provides a distortion-based replication mechanism to support video on-demand services in a dynamic environment, and promotes the advertisement through resourceful peers. We propose a method of estimating video distortion for data stream-chunk replication in the P2P VoD advertising network. The expected amount of distortion reduction in group of pictures (GOP) due to channel conditions can be estimated by the quantity of the received video chunks in a set of resource-sharing peers. The main operating characteristics of the proposed P2P VoD advertising framework includes: (a) an on-demand video repository server, (b) a web portal service, (c) trackers, (d) audience-peers (a set of free-riding peers), and (e) supporting-peers. Repeat the step 2 for the on-demand video from V(t) until the set is empty or there are no available supporting peers
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