Video on-demand streaming on the Internet &amp;#x2014; A survey

Zhang, Xiangyang; Hassanein, H.

doi:10.1109/bsc.2010.5472998

Cited by 7 publications

(10 citation statements)

References 30 publications

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“…Segment requests arrive at a server according to a poisson process with rate λ (requests/minute). For the server selection, we set U ik j to 1/d ik j in Equation (1). A server periodically replaces its cached segments.…”

Section: A Simulation Environment and Metricsmentioning

confidence: 99%

“…With the penetration of broadband Internet to the home, video-on-demand (VoD) service has attracted much attention recently [1], [2]. This is evident from numerous deployed on-demand Internet movie applications, such as hulu.com, pplive.com and netflix.com.…”

Section: Introductionmentioning

confidence: 99%

“…The capacity of each server is heterogeneous, and may not replicate all the contents. 1 As streaming servers, they stream their contents to their local users. 2 Each movie is divided into fixed-sized segments (say, 5-20 minutes).…”

Section: Introductionmentioning

confidence: 99%

“…A home server running a good CR strategy should therefore satisfy most of its segment requests by servers within its proximity (content replication), so as to achieve low interactive delay in accessing the segments 1 For example, the size of a 100-minute movie of bitrate 5 Mbps is around 4GB. To store 10,000 movies, a server requires a capacity of 40TB.…”

Section: Introductionmentioning

confidence: 99%

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Joint optimization of content replication and server selection for video-on-demand

Huang

Xia

Chan

et al. 2012

2012 IEEE International Conference on Communications (ICC)

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Abstract-We study providing large-scale video-on-demand (VoD) service to distributed users. In order to achieve scalability in user capacity and reduce the load of the core network, local servers with heterogeneous storage are deployed. Each server replicates the movie segments depending on their access probabilities. Considering the realistic scenario that underlay delay is a function of the total traffic in the link (including crosstraffic), we address two important problems to achieve low user interactive delay: 1) Which segments should each server replicate under the constraints of their capacities to achieve network-wide good locality effect? This is the so-called content replication (CR) problem; and 2) Given a number of remote servers with the requested segment, which one should serve the user? This is the so-called server selection (SS) problem.CR and SS problems couple with each other. In this paper, we propose a simple and distributed algorithm which seeks to jointly optimize CR and SS. The algorithm, termed CR-SS, achieves good caching locality by adaptively replacing segments and selecting servers with a simple lookup. Simulation results on Internet-like topologies show that CR-SS outperforms existing and state-of-the-art approaches by a wide margin, achieving substantially lower user delay.

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Section: A Simulation Environment and Metricsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Joint optimization of content replication and server selection for video-on-demand

Huang

Xia

Chan

et al. 2012

2012 IEEE International Conference on Communications (ICC)

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“…In order to support a large-scale service, a content provider often deploys content servers close to user pools [4]. We show in Fig.…”

Section: Introductionmentioning

confidence: 99%

Coding Structure and Replication Optimization for Interactive Multiview Video Streaming

Ren

Chan

Cheung

et al. 2014

IEEE Trans. Multimedia

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Abstract-Multiview video refers to videos of the same dynamic 3-D scene captured simultaneously by multiple closely spaced cameras from different viewpoints. We study interactive streaming of pre-encoded multiview videos, where, at any time, a client can request any one of many captured views for playback. Moreover, the client can periodically freeze the video in time and switch to neighboring views for a compelling look-around visual effect. We consider distributed content servers to support large-scale interactive multiview video service. These servers collaboratively replicate and access video contents. We study two challenges in this setting: what is an efficient coding structure that supports interactive view switching and, given that, what to replicate in each server in order to minimize the cost incurred by interactive temporal and view switches? We first propose a redundant coding structure that facilitates interactive view-switching, trading off storage with transmission rate. Using the coding structure, we next propose a content replication strategy that takes advantage of indirect hit to lower view-switching cost: in the event that the exact requested view is not available locally, the local server can fetch a different but correlated view from the other servers, so that the remote repository only needs to supply the pre-encoded view differential. We formulate the video content replication problem to minimize the switching cost as an integer linear programming (ILP) problem and show that it is NP-hard. We first propose an LP relaxation and rounding algorithm (termed Minimum Eviction) with bounded approximation error. We then study a more scalable solution based on dynamic programming and Lagrangian optimization (DPLO) with little sacrifice in performance. Simulation results show that our replication algorithms achieve substantially lower switching cost compared to other content replication schemes. Index Terms-Multimedia

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A Multicast-Enabled Delivery Framework for QoE Assurance of Over-The-Top Services in Multimedia Access Networks

et al. 2013

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Video on-demand streaming on the Internet — A survey

Cited by 7 publications

References 30 publications

Joint optimization of content replication and server selection for video-on-demand

Joint optimization of content replication and server selection for video-on-demand

Coding Structure and Replication Optimization for Interactive Multiview Video Streaming

A Multicast-Enabled Delivery Framework for QoE Assurance of Over-The-Top Services in Multimedia Access Networks

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