Improving VoD server efficiency with bittorrent

Choe, Yung Ryn; Schuff, Derek L.; Dyaberi, Jagadeesh M.; Pai, Vijay S.

doi:10.1145/1291233.1291258

Cited by 82 publications

(44 citation statements)

References 25 publications

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“…• Popularity: The popularity of the segments of the same movie is given by (18) Using the above, we can formulate optimal segment retrieval problem as a linear program (LP-R), i.e.,…”

Section: Lp-r: Optimal Segment Retrieval As a Linear Programmentioning

confidence: 99%

LP-SR: Approaching Optimal Storage and Retrieval for Video-on-Demand

Chan

2013

IEEE Trans. Multimedia

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Abstract-In a distributed large-scale video-on-demand (VoD) streaming network, a content provider often deploys local servers close to their users. A movie is partitioned into segments which the servers collaboratively replicate and retrieve ( ). A critical but challenging problem is how to minimize overall system deployment cost consisting of server bandwidth, server storage, and network traffic among servers. In this paper, we address this problem through jointly optimizing movie storage and retrieval in the server network. We first formulate the optimization problem and show that it is NP-hard. To address the problem, we propose a novel, effective and implementable heuristic termed LP-SR. LP-SR decomposes the optimization problem into two computationally efficient linear programs (LPs) for segment storage and retrieval, respectively. The strength of LP-SR is that it is asymptotically optimal in terms of , and is not high to be closely optimal (around 5 to 10 in our study). For large movie pool, we propose a movie grouping algorithm to further reduce the computational complexity without compromising much on the performance. Through extensive simulation, LP-SR is shown to perform significantly the best as compared with other state-of-the-art and traditional schemes, reducing the deployment cost by a wide margin (by multiple times in many cases). It attains performance very close to the global optimum.Index Terms-Distributed video-on-demand, linear programming, optimization, segment storage and retrieval.

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“…• Popularity: The popularity of the segments of the same movie is given by (18) Using the above, we can formulate optimal segment retrieval problem as a linear program (LP-R), i.e.,…”

Section: Lp-r: Optimal Segment Retrieval As a Linear Programmentioning

confidence: 99%

LP-SR: Approaching Optimal Storage and Retrieval for Video-on-Demand

Chan

2013

IEEE Trans. Multimedia

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“…We propose and study an efficient heuristic to address that. Previous work on replication in video streaming has focused only on single view videos, where there is no correlation among different streams [4], [8]- [10]. Furthermore, the replication strategy in this body of work has not considered the cooperation among neighboring servers to achieve low access cost.…”

Section: Related Workmentioning

confidence: 99%

Coding and replication co-design for interactive multiview video streaming

Huang

Chan

et al. 2012

2012 Proceedings IEEE INFOCOM

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Abstract-Multiview video refers to the simultaneous capturing of multiple video views with an array of closely spaced cameras. In an interactive multiview video streaming (IMVS) system, a client can play back the content in time in a single view, and may observe a scene of interest by switching to different viewpoints. Users independently choose their own view navigation paths through the high-dimensional multiview data. Distributed servers are deployed to collaboratively replicate video content in order to support user scalability. Such a system typically presents challenges in both coding and content replication. In coding, the multiview video must be encoded in order to support efficient viewswitching and distributed replication. In content replication, it is important to decide which data blocks to store at each server to facilitate view-switches at any time.In this paper, we co-design a coding structure and a distributed content replication strategy. First, we propose a coding structure based on redundant P-frames and distributed source coding (DSC) frames to achieve efficiency in coding, view switches and content replication. We then propose a heuristic-based distributed and cooperative replication strategy to take advantage of the correlation between the multiple views for resource-effective content delivery. Simulation results show that our coding and replication codesign is cost-effective in supporting IMVS services.

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“…There has also been related work on piece selection policies that attempt to mediate the conflict between high piece diversity and the in-order requirements of playback (e.g., [12,13,14,15,16]). For example, Annapureddy et al [12] propose splitting each file into fixed-sized segments, each consisting of some number of consecutive pieces.…”

Section: Related Workmentioning

confidence: 99%

“…To increase the likelihood that peers downloading the same segment have pieces to exchange they propose using distributed network coding within segments, and pre-fetch some smaller number of pieces from future segments. Probabilistic piece selection policies have also been proposed [14,15,16]. Note that in order to achieve low start-up delays, these policies depend on older peers uploading to new peers that most likely do not have any needed pieces to offer in exchange.…”

Section: Related Workmentioning

confidence: 99%

Peer-assisted On-demand Video Streaming with Selfish Peers

2009

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Abstract. Systems delivering stored video content using a peer-assisted approach are able to serve large numbers of concurrent requests by utilizing upload bandwidth from their clients to assist in delivery. In systems providing download service, BitTorrent-like protocols may be used in which "tit-for-tat" policies provide incentive for clients to contribute upload bandwidth. For on-demand streaming delivery, however, in which clients begin playback well before download is complete, all prior proposed protocols rely on peers at later video play points uploading data to peers at earlier play points that do not have data to share in return. This paper considers the problem of devising peer-assisted protocols for streaming systems that, similar to download systems, provide effective "tit-for-tat" incentives for clients to contribute upload bandwidth. We propose policies that provide such incentives, while also providing short start-up delays, and delivery of (almost) all video frames by their respective playback deadlines.

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Improving VoD server efficiency with bittorrent

Cited by 82 publications

References 25 publications

LP-SR: Approaching Optimal Storage and Retrieval for Video-on-Demand

LP-SR: Approaching Optimal Storage and Retrieval for Video-on-Demand

Coding and replication co-design for interactive multiview video streaming

Peer-assisted On-demand Video Streaming with Selfish Peers

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