VOVO: VCR-Oriented Video-on-Demand in Large-Scale Peer-to-Peer Networks

He, Yuan; Liu, Yunhao

doi:10.1109/tpds.2008.102

Cited by 44 publications

(5 citation statements)

References 25 publications

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“…The scheme minimizes seeking distortion while gets high utilization ratio. He and Liu [6] adopt the technique of association rule mining to exploit the associations within videos. The segments requested in VCR interactivities are thus predicted according to the information collected through gossips among peers.…”

Section: Related Workmentioning

confidence: 99%

“…When the videos are unpopular or the popular videos are in the initial phase of release, only little seeking statistics can be collected, so the idea of adaptive anchors point [8] and the scheme of mining the association rules of the playback history of a VoD user [6] can hardly acquire ideal SGD. In other words, under the circumstances above, the SGD generated by the above two method cannot satisfy users' VCR request well.…”

Section: Optimized Prefetching Schemementioning

confidence: 99%

“…In the experiment, we generated a synthetic dataset of user viewing logs according to the playing frequency of segments in the video and the cumulative distribution of peers' number of VCR controls in [6]. The accumulated playing frequency of segments in the video conforms to the distribution in Fig.…”

Section: Performance Evaluationmentioning

confidence: 99%

“…Many existing works have discussed how to tackle VCR interactivity problem. From previous research, we can know there are mainly two methods which can reduce the seeking latency of VCR controls: first, optimizing the index overlay to realize fast segment relocation [2] [3] [4]; second, prefetching appropriate segments and improving hit ratio [6]- [9] [11] [12]. The hit ratio is defined as the probability with which the VCR requests are satisfied by the prefetched content.…”

Section: Introductionmentioning

confidence: 99%

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Optimized Prefetching Scheme to Support VCR-Like Operations in P2P VoD Applications with Guided Seeks

Jiang

Zhang

Liu

2015

AMM

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In Peer-to-Peer (P2P) Video-on-Demand (VoD) streaming systems, supporting free VCR operations is challenging. Prefetching is a good way to improve user experience of VCR interactivity. But most existing P2P VoD prefetching schemes are proposed aimed at those popular videos with large amount of log data, without considering the situation that the videos are unpopular or the popular videos are in their initial phase of release. In this situation, these schemes cannot support user VCR interactivity very well. To address this issue, we propose a new optimized prefetching scheme, called Hybrid Anchor Scheme (HAS), in which fixed anchors and dynamic anchors are merged together. The dynamic anchors are generated based on association rule and segments popularity. Through combining the way of sequential prefetching according to weight of segments and the way of several rounds prefetching, we implement HAS effectively. Extensive simulations validate the proposed prefetching scheme provide shorter seeking latency compared to other prefetching schemes.

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Section: Related Workmentioning

confidence: 99%

Section: Optimized Prefetching Schemementioning

confidence: 99%

Section: Performance Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimized Prefetching Scheme to Support VCR-Like Operations in P2P VoD Applications with Guided Seeks

Jiang

Zhang

Liu

2015

AMM

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“…Recently, some studies on P2P VoD systems [8][9][10][11][12][13][14][15][16] have emphasized the support to VCR-like operations and can handle the random seeks. Most of these studies have applied a hybrid overlay.…”

Section: Introductionmentioning

confidence: 99%

An Adapted Multi-way Tree with Holder-chain for Large Scale P2P VoD System

Liu¹,

Huang²,

Zhou³

et al. 2013

Proceedings of 3rd International Conference on Multimedia Technology(ICMT-13)

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Abstr act. Peer-to-Peer Video-on-demand (P2P VoD) systems have attracted great interest in research community. Many hybrid methods have been proposed to provide high-quality video-on-demand services to support VCR-like operations, which can scale to large population of users. In this paper, we propose a hybrid overlay DONet-AMT, which combines DONet and an adapted multi-way tree. DONet is applied to distribute the video segments efficiently. The adapted multiway tree consists of two layers: a complete multi-way tree and holder-chain, which can support efficient VCR-like operations. Our scheme can ensure that every video segment has k (typically k≥4) replicas at least when the number of peers is large enough, and thus guarantees high data availability. Finally, the performance analysis shows that DONet-AMT can provide better VoD services than DONet-VoD. With the prevalence of broadband Internet access, VoD services over the Internet have become increasingly popular. The traditional client-server architecture can hardly scale to a large population of users due to the limited service capacity of the servers. Recent years, P2P networks have been shown to be a promising approach to provide high scalability VoD streaming service [1][2][3][4][5][6][7][8].In the P2P VoD systems, supporting VCR-like operations such as jump forward/backward is a great challenge. The VCR-like operations result in frequent seeking, and thus can impose great impacts on the viewing quality. We can define seeking latency as the interval between the time when a segment is requested and the time when the segment is ready for playback. To achieve a high viewing quality, the seeking latency must be as short as possible. To reduce the seeking latency,

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Probabilistic Seeking Prediction in P2P VoD Systems

Wang

2009

AI 2009: Advances in Artificial Intelligence

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Abstract. In P2P VoD streaming systems, user behavior modeling is critical to help optimise user experience as well as system throughput. However, it still remains a challenging task due to the dynamic characteristics of user viewing behavior. In this paper, we consider the problem of user seeking prediction which is to predict the user's next seeking position so that the system can proactively make response. We present a novel method for solving this problem. In our method, frequent sequential patterns mining is first performed to extract abstract states which are not overlapped and cover the whole video file altogether. After mapping the raw training dataset to state transitions according to the abstract states, we use a simpel probabilistic contingency table to build the prediction model. We design an experiment on the synthetic P2P VoD dataset. The results demonstrate the effectiveness of our method.

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VOVO: VCR-Oriented Video-on-Demand in Large-Scale Peer-to-Peer Networks

Cited by 44 publications

References 25 publications

Optimized Prefetching Scheme to Support VCR-Like Operations in P2P VoD Applications with Guided Seeks

Optimized Prefetching Scheme to Support VCR-Like Operations in P2P VoD Applications with Guided Seeks

An Adapted Multi-way Tree with Holder-chain for Large Scale P2P VoD System

Probabilistic Seeking Prediction in P2P VoD Systems

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