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Studies On Rate Control, Performance Enhancing And Scheduling In Multicasting Video Over The Internet

Posted on:2003-10-15Degree:DoctorType:Dissertation
Country:ChinaCandidate:H WangFull Text:PDF
GTID:1118360122967314Subject:Computer application technology
Abstract/Summary:PDF Full Text Request
Multicasting video over the Internet is an important component for various modern multimedia communicating applications. Although video multicasting shows a promising future, it has to overcome two main obstacles, 1. Current Internet infrastructure can not guarantee the Qualility of Service for video streaming, and 2. The networks and users connected to them show enormous heterogeneity. Many problems are still remained in this area and more research work is expected.Combining with new video coding techniques and emerging network protocols, this paper focuses on three research topics in multicasting video over the Internet. These topics are: 1. Fine-grained rate adaptive video multicasting algorithms, 2. Using peer-to-peer techniques to enhance the performance of application-level video multicasting, and 3. Scheduling strategies based on stream-merging using video multicasting techniques.The creativities and contributions are discussed in detail as follows:1. This paper proposes a fine-grained rate adaptive dynamic-layering video multicasting framework - FGAVM. Among current video multicasting algorithms, Replicated-Stream Multicast adapts the rate well according to network dynamics, but its bandwidth efficiency is poor; On the other hand, Layered Video Multicast has high bandwidth efficiency but its adaption is poor. To bring all the merits of existing alortithms together while avoiding their drawbacks, this paper harnesses the power of FGS video coding technique to propose a new video multicasting framework - FGAVM. FGAVM adopts a hybrid of centralized and de-centralized strategies to adjust the bitrate of each multicast channel according to network dynamics with fine granularity. Extensive simulation results show that FGAVM can fine-tune the bitrate and also achieve high bandwidth efficiency. Moreover, FGAVM can provide inter-session fairness and TCP friendliness thus is a better framework for Internet video multicasting.2. Using peer-to-peer techniques, this paper proposes a new application-level video multicasting architecuture called P3S,. Inspired by the emerging peer-to-peer file sharing service on the Internet, this paper extends the delivery tree structure of current application-level video multicasting and proposes a grid-based hierarchical architecture - P3S. In P3S, service subscribers can cooperate with each other by using peer-to-peer techniques. This paper concentrates on two cooperative techniques between service subscribers in P3S: Error Recovery and Data Allocation. Error recovery technique aims at decreasing the overall packet loss ratio by interchangingdata between subscribers. In order to combat the impact of correlative packet losses, this paper proposes to introduce some controlled delay between two unicast sessions originated from the same intermediate P3S node. Both theoretical and experimental results support the proposed technique. Data Allocation means that the source node of each P3S grid allocates different part of the the video content for each downstream receivers according to the bandwidth between them. After the cooperation between the two receivers, each receiver can achieve higher data thoughput. In this paper, we propose a technique, based on linear programming that optimally allocates the content so that the total throughput of the whole session is maximized. We also present a greedy data allocation algorithm that is slightly suboptimal but much simpler. The simulation results show that, compared with current application-level video multicasting methods, P3S with the techniques we proposed has the advantages of lower packet loss ratio, higher overall data throughput and higher quality of video image, thus can provide better performance for Internet video multicasting.3.Based on video multicasting techniques, this paper proposes a new scheduling strategy called Patching First. Patching First improves the performance of current Patching algorithm by serving user requests differently according to their different types. By allocating resources for low-co...
Keywords/Search Tags:ideo Multicasting, Fine Gruanular Scalable, Application-Level Multicast, Peer-to-Peer, Stream-Merging.
PDF Full Text Request
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