582 research outputs found

    Distributed Bandwidth-efficient Packet Scheduling for Live Streaming with Network Coding

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    Bandwidth-Efficient Packet Scheduling for Live Streaming With Network Coding

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    Semi-fluid: A Content Distribution Model For Faster Dissemination Of Data

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    Tesis ini mencadangkan serta melaksanakan suatu model agihan kandungan bagi mengurangkan atau meminimumkan kelengahan penyaluran data sebaya. Buat masa ini, agihan kandungan dalam rangkaian tindihan-atas adalah berdasarkan dua model berikut: model Kelulan dan model Bendalir. This thesis proposes and implements a novel content distribution model for reducing or minimizing delay in data dissemination

    Bandwidth-efficient Video Streaming with Network Coding on Peer-to-Peer Networks

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    PhDOver the last decade, live video streaming applications have gained great popularity among users but put great pressure on video servers and the Internet. In order to satisfy the growing demands for live video streaming, Peer-to-Peer(P2P) has been developed to relieve the video servers of bandwidth bottlenecks and computational load. Furthermore, Network Coding (NC) has been proposed and proved as a significant breakthrough in information theory and coding theory. According to previous research, NC not only brings substantial improvements regarding throughput and delay in data transmission, but also provides innovative solutions for multiple issues related to resource allocation, such as the coupon-collection problem, allocation and scheduling procedure. However, the complex NC-driven P2P streaming network poses substantial challenges to the packet scheduling algorithm. This thesis focuses on the packet scheduling algorithm for video multicast in NC-driven P2P streaming network. It determines how upload bandwidth resources of peer nodes are allocated in different transmission scenarios to achieve a better Quality of Service(QoS). First, an optimized rate allocation algorithm is proposed for scalable video transmission (SVT) in the NC-based lossy streaming network. This algorithm is developed to achieve the tradeoffs between average video distortion and average bandwidth redundancy in each generation. It determines how senders allocate their upload bandwidth to different classes in scalable data so that the sum of the distortion and the weighted redundancy ratio can be minimized. Second, in the NC-based non-scalable video transmission system, the bandwidth ineffi- ciency which is caused by the asynchronization communication among peers is reduced. First, a scalable compensation model and an adaptive push algorithm are proposed to reduce the unrecoverable transmission caused by network loss and insufficient bandwidth resources. Then a centralized packet scheduling algorithm is proposed to reduce the unin- formative transmission caused by the asynchronized communication among sender nodes. Subsequently, we further propose a distributed packet scheduling algorithm, which adds a critical scalability property to the packet scheduling model. Third, the bandwidth resource scheduling for SVT is further studied. A novel multiple- generation scheduling algorithm is proposed to determine the quality classes that the receiver node can subscribe to so that the overall perceived video quality can be maxi- mized. A single generation scheduling algorithm for SVT is also proposed to provide a faster and easier solution to the video quality maximization function. Thorough theoretical analysis is conducted in the development of all proposed algorithms, and their performance is evaluated via comprehensive simulations. We have demon- strated, by adjusting the conventional transmission model and involving new packet scheduling models, the overall QoS and bandwidth efficiency are dramatically improved. In non-scalable video streaming system, the maximum video quality gain can be around 5dB compared with the random push method, and the overall uninformative transmiss- sion ratio are reduced to 1% - 2%. In scalable video streaming system, the maximum video quality gain can be around 7dB, and the overall uninformative transmission ratio are reduced to 2% - 3%

    Exploring a QoS Driven Scheduling Approach for Peer-to-Peer Live Streaming Systems with Network Coding

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    Most large-scale peer-to-peer (P2P) live streaming systems use mesh to organize peers and leverage pull scheduling to transmit packets for providing robustness in dynamic environment. The pull scheduling brings large packet delay. Network coding makes the push scheduling feasible in mesh P2P live streaming and improves the efficiency. However, it may also introduce some extra delays and coding computational overhead. To improve the packet delay, streaming quality, and coding overhead, in this paper are as follows. we propose a QoS driven push scheduling approach. The main contributions of this paper are: (i) We introduce a new network coding method to increase the content diversity and reduce the complexity of scheduling; (ii) we formulate the push scheduling as an optimization problem and transform it to a min-cost flow problem for solving it in polynomial time; (iii) we propose a push scheduling algorithm to reduce the coding overhead and do extensive experiments to validate the effectiveness of our approach. Compared with previous approaches, the simulation results demonstrate that packet delay, continuity index, and coding ratio of our system can be significantly improved, especially in dynamic environments
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