Providing scalable on-demand interactive video service by means of multicasting and client buffering

Chan, S.-H. Gary; Chang, Edward Yi

doi:10.1109/icc.2001.937191

Cited by 3 publications

(3 citation statements)

References 24 publications

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“…where P kn can be calculated by (14). Consider the general case from time 0 to t. We derive the required average server bandwidth by modeling the system as a renewal process.…”

Section: Analysis For the Required Server Bandwidthmentioning

confidence: 99%

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Medusa: A Novel Stream-Scheduling Scheme for Parallel Video Servers

Jin

Deng

Pang

2004

EURASIP J. Adv. Signal Process.

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Parallel video servers provide highly scalable video-on-demand service for a huge number of clients. The conventional stream-scheduling scheme does not use I/O and network bandwidth efficiently. Some other schemes, such as batching and stream merging, can effectively improve server I/O and network bandwidth efficiency. However, the batching scheme results in long start-up latency and high reneging probability. The traditional stream-merging scheme does not work well at high client-request rates due to mass retransmission of the same video data. In this paper, a novel stream-scheduling scheme, called Medusa, is developed for minimizing server bandwidth requirements over a wide range of client-request rates. Furthermore, the start-up latency raised by Medusa scheme is far less than that of the batching scheme.

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“…where P kn can be calculated by (14). Consider the general case from time 0 to t. We derive the required average server bandwidth by modeling the system as a renewal process.…”

Section: Analysis For the Required Server Bandwidthmentioning

confidence: 99%

“…For CIWP [5,13,14,15,16,17], the complete multicast stream is scheduled when a client request arrives. The latest complete multicast stream for the same video object cannot be received by that client.…”

Section: Related Workmentioning

confidence: 99%

Medusa: A Novel Stream-Scheduling Scheme for Parallel Video Servers

Jin

Deng

Pang

2004

EURASIP J. Adv. Signal Process.

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“…(A certain degree of user interactivity may be achieved with near-VOD. Readers interested in this aspect are referred to [4]- [6] and the references therein.) Today, request batching is widely used for movie-on-demand services over satellite and cable networks.…”

Section: Introductionmentioning

confidence: 99%

Tradeoff between system profit and user delay/loss in providing near video-on-demand service

Chan

Tobagi

2001

IEEE Trans. Circuits Syst. Video Technol.

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In a near video-on-demand (near-VOD) system, requests for a movie arriving in a period of time are grouped (or "batched") together and served with a single multicast stream. In this paper, we consider providing near-VOD services when there is a cost associated with using a network multicast channel. We address the tradeoff between system profit, given by the total pay-per-view collected minus the total channel cost, and user delay or user loss (due to reneging). We first analyze and compare the tradeoff of two traditional "basic" schemes, namely, the window-based schemes in which a maximum user delay can be guaranteed, and the batch-size based scheme in which system profit can be guaranteed. By combining these basic schemes, we present a scheme which can adaptively balance system profit and user delay when the underlying request rate fluctuates. We then consider the case in which delayed users may renege and determine how system profit can be maximized by sizing the batching period given user's reneging behavior. We show that maximizing profit can lead to excessively high user loss rate, especially when the channel cost is high and users are not very patient. Therefore, a shorter suboptimal batching period should be used for this case in reality. We finally introduce schemes which are able to offer high profit or low user loss when the underlying arrival rate fluctuates.Index Terms-Multicasting, near video-on-demand, request batching, system profit, user delay, user loss.

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A Dynamically Grouped Multi-multicast Stream Scheduling Strategy for Video-on-Demand Systems

Deng

Jin

Han

2003

Lecture Notes in Computer Science

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Abstract. Network bandwidth is the key performance bottleneck for a videoon-demand (VoD) server. It controls the number of clients the server can support simultaneously. Previous works have shown some strategies, such as the batching strategy and the stream merging strategy, that use one multicast stream to serve different clients requesting the same video object at the same time. They improve the performance of server bandwidth effectively. But the batching strategy results in long start-up latency and the traditional stream merging strategy also wastes lots of server bandwidth. In this paper, we propose a dynamically grouped multi-multicast stream scheduling strategy, called DGMM, and analyze its performance in two factors: the start-up latency and the average bandwidth consumption.

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Providing scalable on-demand interactive video service by means of multicasting and client buffering

Cited by 3 publications

References 24 publications

Medusa: A Novel Stream-Scheduling Scheme for Parallel Video Servers

Medusa: A Novel Stream-Scheduling Scheme for Parallel Video Servers

Tradeoff between system profit and user delay/loss in providing near video-on-demand service

A Dynamically Grouped Multi-multicast Stream Scheduling Strategy for Video-on-Demand Systems

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