Optimal Prefetching Scheme in P2P VoD Applications With Guided Seeks

He, Yejun; Shen, Guobin; Xiong, Yan; Guan, Ling

doi:10.1109/tmm.2008.2008929

Cited by 37 publications

(7 citation statements)

References 32 publications

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“…High-level media data decoding depends on the lower-level media data, so media data at low level should have higher priority. [11] pointed out that the request priority mechanism of scarcity data block ensure the diversity of the data block in overlay network, which is conducive to large-scale exchange of data between nodes. In order to enable the process of data block distribution faster and smoother in the whole overlay network, data block priority should include playback of the data block cut-off time, the scarcity of data blocks, block level where the media are included.…”

Section: Related Workmentioning

confidence: 99%

P2P VoD Content Distribution Strategy Based on Gradient Model

Dai

Wang

Tang

2013

AMR

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The characteristics of P2P VoD (Video on Demand) system, such as low cost, great scalability and high quality of service, make it become the research hotspots and development trends of current network applications, while content distribution policy is one of its key technologies. To solve the problems of data scheduling strategy priority and node performance discrepancy in content distribution, the influences on scheduling policies of network performance information, the degree of content scarcity and playback emergency were studied. Based on the investigation, the gradient model based content distribution strategy is proposed. Distributed gradient model based strategy, sender startup strategy and receiver startup strategy were introduced to make each peer merely interact with parts of peers to reduce the collisions caused by the load balance. The experimental results show that gradient model based content distribution strategy improves the delivery speed and reduces the network load.

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Section: Related Workmentioning

confidence: 99%

P2P VoD Content Distribution Strategy Based on Gradient Model

Dai

Wang

Tang

2013

AMR

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“…The objective of the work, together with the recent work on peer-to-peer VoD [21]- [24], is to fully utilize the uploading bandwidth of the peers. The work in [25], [26] presents heuristics to efficiently search for movie segments in order to support user interactivity. All the work in [15]- [26] has not considered the optimal movie storage and retrieval to minimize the deployment cost due to bandwidth and storage.…”

Section: Related Workmentioning

confidence: 99%

“…The work in [25], [26] presents heuristics to efficiently search for movie segments in order to support user interactivity. All the work in [15]- [26] has not considered the optimal movie storage and retrieval to minimize the deployment cost due to bandwidth and storage. Our work presents an asymptotically optimal solution for a novel VoD network.…”

Section: Related Workmentioning

confidence: 99%

“…In this section, we present the cost-optimization problem of our VoD network for the asymptotic case given movie popularity (how to estimate movie popularity is beyond the scope of this work. Interested readers may refer to [25], [26], [34] and references therein). For this case, the optimization becomes an LP which can be solved efficiently and exactly.…”

Section: B a Linear Programming Formulationmentioning

confidence: 99%

“…. Proof: From ( 5) and (12) we get (26) If is not the repository, is rounded up or down by at most 1. Therefore, (27) Consider the worst case that, for a server , is rounded down by 1 and .…”

Section: Appendix B B Proof Of Asymptotic Optimality Of Bucket-fillingmentioning

confidence: 99%

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Bucket-filling : an asymptotically optimal video-on-demand network with source coding

Chang¹

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There has recently been growing interest for content providers to provide video-on-demand (VoD) as a cloud service. In such a network, the content provider may rent heterogeneous resources (such as streaming and storage capacities) from geographically distributed data centers deployed close to user pools. These data centers (or proxy servers) collaboratively share content with each other to serve their local users. A critical challenge is to optimize movie storage and retrieval to minimize the deployment cost consisting of streaming, storage, and network transmission between data centers. We propose a novel and effective movie storage and retrieval using linear source coding. All the movies are source-encoded once at the repository, by taking every source symbols of movie to generate coded symbols. These coded symbols are then distributed to the servers in the cloud. Based on a general and comprehensive cost model, we optimize and the number of symbols to retrieve from remote servers for a local movie request. The optimal solution can be efficiently computed with a linear programming (LP) formulation. Our solution is proved to asymptotically approach the global minimum cost as increases. Even when is low, near optimality can be achieved. To accommodate large movie pool and system parameter changes, we propose algorithms for movie grouping and on-line re-optimization which significantly reduce the computational complexity with little compromise on optimality. Through extensive simulation, our algorithm is shown to achieve the lowest cost, outperforming traditional and state-of-the-art heuristics with a substantially wide margin.

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SeekStream: adapting to dynamic user behavior in P2P video‐on‐demand

Deltouzos

Gkortsilas

Efthymiopoulos

et al. 2016

Int J Communication

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In recent years, the users' perceived quality of experience (QoE) in streaming services has gained a lot of attention. Particularly, a number of research efforts have focused on providing live streaming and video-ondemand (VoD) services using peer-to-peer (P2P) architectures. However, in these proposed architectures, the heterogeneity of users and their dynamic behavior has not been sufficiently studied. In a real life scenario, where users have highly heterogeneous bandwidth resources (cable, DSL, 3G networks, etc) and can arbitrarily decide to perform a VCR function (stop, fast forward and seeking), ignoring this behavior can significantly deteriorate the system's efficiency and the perceived QoE. In this paper, we present SeekStream, a scalable P2P VoD architecture that ensures the stable delivery of the video stream to every participating user even in cases of high heterogeneity and frequent seeking operations. Specifically, SeekStream is a set of algorithms that optimize the P2P overlay dynamically and in a distributed fashion, making it adaptive to users dynamic behavior and bandwidth changes. The available bandwidth resources of the participating users are optimally exploited, keeping the contribution from the media server(s) to a minimal level. To illustrate the performance of the proposed algorithms, we are using a centralized overlay network manager that discovers the optimal network graph as a reference. We have developed an extensive P2P VoD simulator that shows the efficiency, scalability, and stability of our system under variant and dynamic conditions. The algorithms of our proposed system introduce less than 4% bandwidth overhead while we achieve high offloading of the media server(s). SeekStream guarantees a high block reception rate for the users, even under extreme seeking patterns.In P2P streaming services, each media object (video) is assumed to have a certain average playback rate and is usually divided into blocks of equal size. Peers that are interested to watch the video may enter the system at arbitrary time instants and consume the video fraction(s) of their interest.Adequate space is allocated in each peer's hard disk for the purpose of saving these blocks, which are provided either directly from the media server or from the participating peers. Generally, peers join the system and watch the video sequentially. However, it is not uncommon for someone to skip one or more parts of the video that are of no interest to it.For example, in Figure 1, we depict the hard disk of peer i watching a video of 64 blocks. Peer i joined the system and opted to watch the video not from its beginning, but starting from block 5. Then after having watched until block 12, it jumped to block 17, then from 28 to 37. Its current playback point is block 50 at time t 0 . Because of the jumps, we can see that the white blocks have not been requested, thus creating blank areas, whereas the blocks that are pending (requested but not yet delivered) and received are orange and green respectively. Different video par...

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Optimal Prefetching Scheme in P2P VoD Applications With Guided Seeks

Cited by 37 publications

References 32 publications

P2P VoD Content Distribution Strategy Based on Gradient Model

P2P VoD Content Distribution Strategy Based on Gradient Model

Bucket-filling : an asymptotically optimal video-on-demand network with source coding

SeekStream: adapting to dynamic user behavior in P2P video‐on‐demand

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