A Measurement Study of Cache Rejection in P2P Live Streaming System

Chen, Yishuai; Chen, Changjia; Li, Chunxi

doi:10.1109/icdcs.workshops.2008.49

Cited by 18 publications

(11 citation statements)

References 7 publications

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“…In [27], authors derive the performance bounds with regards to the minimum server load, maximum streaming rate, and minimum tree depth. [28] models the cache rejection algorithm in PPLive as a fixed-duration virtual buffer. A common weakness is that they focus only on particular applications and they never investigate what will happen if different streaming service providers collaborate with each other.…”

Section: Related Workmentioning

confidence: 99%

Enriching Viewer Options in P2P Media Streaming Applications

Wang

Shen

Luo

et al. 2009

2009 29th IEEE International Conference on Distributed Computing Systems Workshops

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Peer-to-Peer (P2P) media streaming applications are increasingly popular on the Internet and offer a wide variety of media content, attracting potentially millions of viewers simultaneously. However, much content is duplicated, synchronously and asynchronously: popular Hollywood movies are often offered by many different on-demand streaming service providers; live streaming service providers distribute the same media content, for instance television series, in different channels over a delay of some hours or days.Viewers are more concerned about the media content and the quality of the streaming service, and less about who is actually offering it. In this article we aim at enriching the viewers' options instead of focusing on particular streaming applications: 1) we present a general content service facilitating the viewers to share their choices of what, when and where they will watch; 2) we extend streaming clients to accommodate various behaviors of the viewers besides their traditional operations. As such, the viewers will get a better experience, and streaming service providers and Internet service providers both have an opportunity to cut down their resource consumption.

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Section: Related Workmentioning

confidence: 99%

Enriching Viewer Options in P2P Media Streaming Applications

Wang

Shen

Luo

et al. 2009

2009 29th IEEE International Conference on Distributed Computing Systems Workshops

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“…In order to relax the time requirements, to have enough time to react to node failures and to smooth out the jitter, packets flow through two buffers: one is managed by PPLive, and the second by the media player. A downside of such architecture is the long start-up delay [78]. The working of PPStream is very similar to PPLive.…”

Section: Popular Mesh-based Live Streaming Systemsmentioning

confidence: 99%

P2P Video Streaming

Thampi¹

2013

Building Next-Generation Converged Networks

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The main objective of this article is to provide an overview of P2P based Video-on-Demand and live streaming services. The article starts with an introduction to media streaming and its simplified architecture. Various solutions offering video streaming in the context of widespread usage of Internet are discussed. This is followed by a short introduction to P2P networks and its applications. A broad discussion on various P2P streaming schemes and P2P streaming applications are the main focus of this chapter. Finally, the security issues and solutions for P2P video streaming are discussed briefly.Typically, for streaming video, congestion control takes the form of rate control. Rate control attempts to minimize the possibility of network congestion by matching the rate of the video stream to the available network bandwidth. Based on the place where rate control is taken in the system, rate control can be categorized into three types: sourcebased, receiver-based and hybrid-based. With the source-based rate control, only the sender (server) is responsible for adapting the transmission rate. In contrast, the receiving rate of the streams is regulated by the client in the receiverbased method. Hybrid-based rate control employs the aforementioned schemes at the same time, i.e. both the server and client are needed to participant in the rate control. Typically, the source-based scheme is used in either unicast or multicast environment while the receiver-based method is deployed in multicast only [6].The function of error control is to improve video presentation quality in the presence of packet loss. Error control mechanisms include Forward Error Correction (FEC), retransmission, error-resilient encoding and error concealment. With FEC scheme, the received packets at the receiver end are FEC decoded and unpacked, and the resulting bit stream is then input to the video decoder to reconstruct the original video. Error-resilient encoding is executed by the source to enhance robustness of compressed video before packet loss actually happens. Even when an image sample or a block of samples are missing due to transmission errors, the decoder can try to estimate them based on surrounding received samples, by making use of inherent correlation among spatially and temporally adjacent samples, such techniques arc known as error concealment techniques [14]. Media distribution services:After the adaptation by application-layer QoS control module, the transport protocols packetize the compressed bit-streams and send the video/audio packets to the Internet. Packets may be dropped or experience excessive delay inside the Internet due to congestion. In addition to the application-layer support, adequate network support is necessary to reduce transport delays and packet losses. The network support involves network filtering, application-level multicast and content replication (caching). Network filtering maximizes video quality during network congestion. The filter at the video server can adapt the rate of video streams according to the...

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“…Through analyzing and modeling, we ever characteristic PPLive on several aspects, including its chunk based buffer policy, the Proportional Placement scheme based initial phase decision [4], sequential fetching and rarest first based chunk fetching [7], etc. On the other hand, we ever evaluate the performance of early version of PPStream, and reveal features on geographic clustering, topology, and arrival/departure pattern in 2007 [2]; Recently WeiTing at [1] presents some simple description on PPStream's buffer schedule, and provides a preliminary analysis on the startup progress for the new version of PPStream; Report of [3] focuses on the privacy, locality.…”

Section: Introductionmentioning

confidence: 99%

Measurement based PPStream client behavior analysis

Chen

2009

2009 ISECS International Colloquium on Computing, Communication, Control, and Management

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PPStream is one of the most popular p2p media streaming applications. Our early study finds the design philosophy for both PPStream and PPLive is different. As a preliminary study for further deeply modeling, in this paper we try to study PPStream client behavior based on our recent measurement dataset. The report focuses on several aspects of peer: some specific mechanisms applied in the new version of PPStream client; overlay network environment of the system including the round-trip time, packet loss and replication; the concurrency of sessions, fetching buffer blocks and chunks; the chunk fetching behavior as well as the reciprocity between our client and its neighbors. We think our finds and discussions are of great values to further studies for researchers.

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A Measurement Study of Cache Rejection in P2P Live Streaming System

Cited by 18 publications

References 7 publications

Enriching Viewer Options in P2P Media Streaming Applications

Enriching Viewer Options in P2P Media Streaming Applications

P2P Video Streaming

Measurement based PPStream client behavior analysis

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