Multicast with cache (Mcache): an adaptive zero-delay video-on-demand service

Ramesh, S.; Rhee, Injong; Guo, Katherine

doi:10.1109/76.911167

Cited by 77 publications

(51 citation statements)

References 17 publications

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“…The idea of utilizing client-side caching has been proposed in several previous work [21,19,14,16]. The authors of [6] propose an overlay, multicast strategy, oStream, that leverages client-side caching to reduce the server bandwidth as well as the network link cost.…”

Section: Related Workmentioning

confidence: 99%

Performance Evaluation of Distributed Prefetching for Asynchronous Multicast in P2P Networks

Sharma

Bestavros

Matta

2004

Web Content Caching and Distribution

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Abstract. We consider the problem of delivering real-time, near realtime and stored streaming media to a large number of asynchronous clients. This problem has been studied in the context of asynchronous multicast and peer-to-peer content distribution. In this paper we evaluate through extensive simulations the performance of the distributed prefetching protocol, dPAM [20], proposed for scalable, asynchronous multicast in P2P systems. We show that the prefetch-and-relay strategy of dPAM can reduce the server bandwidth requirement quite significantly, compared to the previously proposed cache-and-relay strategy, even when the group of clients downloading a stream changes quite frequently due to client departures.

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Section: Related Workmentioning

confidence: 99%

Performance Evaluation of Distributed Prefetching for Asynchronous Multicast in P2P Networks

Sharma

Bestavros

Matta

2004

Web Content Caching and Distribution

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“…As such, a single encoded version of an object would match the bandwidth and format demands of all requests to the object. According to the selection of the portions to cache, we can classify existing algorithms into four categories: sliding-interval caching [2,6,21], prefix caching [10,14,19], segment caching [4,8,28], and rate-split caching [26]. Our scheme is particularly related to the ratesplit caching in the sense that we also partition the stream along the rate axis.…”

Section: Previous Workmentioning

confidence: 99%

“…There has been plenty of works devoted to streaming media caching [1,2,4,[6][7][8]10,12,14,19,[21][22][23]26,28]. Most of them target homogeneous clients, which have identical or similar configurations and capabilities behind a proxy.…”

Section: Previous Workmentioning

confidence: 99%

A QoS-Based Joint Scheduling and Caching Algorithm for Multimedia Objects

Liu

2004

World Wide Web

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With the development of the broadband Internet, multimedia services have been widely deployed and contributed to a significant amount of today's Internet traffic. Like normal web objects (e.g., HTML pages and images), media objects can benefit from proxy caching; yet their unique features such as huge size and high bandwidth demand imply that conventional proxy caching strategies have to be substantially revised. Moreover, in the current Internet, clients are highly heterogeneous; it is necessary to differentiate their Quality-of-Service (QoS) requirements in streaming. However, the presence of an intermediate proxy in a streaming system poses great challenges to designers. This paper proposes a novel QoS-based algorithm for media streaming with proxy caching. We employ layered coding and transmission, and jointly consider the problems of caching and scheduling to improve the QoS for the clients. We derive general and effective solutions to the problems and evaluate their performance under various configurations. The results demonstrate that the proposed algorithm can accommodate diverse QoS demands from the clients, and yet satisfy stringent resource limits.

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“…There has been a rich body of work on on-demand streaming which roughly fall into two categories: multicast-based techniques [12,15,9,8] and media caching [20,3,23,4]. MetaStream is closely related to several recent work on client-side media caching [5,6,14].…”

Section: Related Workmentioning

confidence: 99%

“…Due to the synchronous nature of multicast, clients either wait for the next scheduled multicast session at the cost of some start-up delay [9,12], or participate in more than one sessions simultaneously [15,8]. The second approach exploits caching of media objects at the proxies [20,3,21], or at the clients [23,7,14,5,6]. The media can be retrieved from the caches instead of from the streaming server.…”

Section: Introductionmentioning

confidence: 99%

Topology-Aware Peer-to-Peer On-demand Streaming

Zhang

Butt

2005

NETWORKING 2005. Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile A

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Abstract. In this paper, we consider large-scale high-bandwidth on-demand media streaming in a dynamic and heterogeneous environment. We present MetaStream, a scalable and distributed content discovery protocol that enables clients across the Internet to self-organize into a topology-aware overlay network, in which they can "cache and relay" a stream among nearby peers. We present the design and implementation of MetaStream and show experimental results obtained in a large-scale emulated environment. Our evaluation shows that MetaStream distributes relaying load among the clients in a topology-aware manner, imposing low link cost to the underlying network and low streaming load on the media server. MetaStream is also highly resilient to node or network failures and is capable of quickly recovering the streaming quality at clients even at high failure rates.

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Multicast with cache (Mcache): an adaptive zero-delay video-on-demand service

Cited by 77 publications

References 17 publications

Performance Evaluation of Distributed Prefetching for Asynchronous Multicast in P2P Networks

Performance Evaluation of Distributed Prefetching for Asynchronous Multicast in P2P Networks

A QoS-Based Joint Scheduling and Caching Algorithm for Multimedia Objects

Topology-Aware Peer-to-Peer On-demand Streaming

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