A distributed real-time MPEG video audio player

Cen, Shanwei; Pu, Calton; Staehli, Richard; Cowan, Crispin; Walpole, Jonathan

doi:10.1007/bfb0019263

Cited by 92 publications

(51 citation statements)

References 5 publications

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“…For example, the work presented in [26] and [3] uses software feedback mechanisms that enhance system adaptiveness by adjusting video sending rate according to on-the-fly network variations. In [27], Hafid et al propose application adaptation at the configuration level, which carries out transparent transition from primary components to alternative components, as well as at the component level, which redistributes resources in different components so that a QoS tradeoff can be made.…”

Section: Application-specific Mechanismsmentioning

confidence: 99%

A control-based middleware framework for quality-of-service adaptations

Nahrstedt

1999

IEEE J. Select. Areas Commun.

261

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Abstract-In heterogeneous environments with performance variations present, multiple applications compete and share a limited amount of system resources, and suffer from variations in resource availability. These complex applications are desired to adapt themselves and to adjust their resource demands dynamically. On one hand, current adaptation mechanisms built within an application cannot preserve global properties such as fairness; on the other hand, adaptive resource management mechanisms built within the operating system are not aware of data semantics in the application.In this paper, we present a novel Middleware Control Framework to enhance the effectiveness of QoS adaptation decisions by dynamic control and reconfiguration of internal parameters and functionalities of a distributed multimedia application. Our objective is to satisfy both system-wide properties (such as fairness among concurrent applications) and application-specific requirements (such as preserving the critical performance criteria). The framework is modeled by the Task Control Model and the Fuzzy Control Model, based on rigorous results from the control theory, and verified by the controllability and adaptivity of a distributed visual tracking application. The results show validation of the framework, i.e., critical application quality parameter can be preserved via controlled adaptation.

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Section: Application-specific Mechanismsmentioning

confidence: 99%

A control-based middleware framework for quality-of-service adaptations

Nahrstedt

1999

IEEE J. Select. Areas Commun.

261

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“…These formats do not provide explicit support for adapting rate after encoding. Frame dropping is a well known work-around, and is probably the most popular video adaptation mechanism, having been used since the first quality-adaptive Internet streaming systems appeared [3]. Windows Media and RealSystem include mechanisms for adaptive streaming, called Intelligent Streaming (IntelliStream) and SureStream respectively [7,1].…”

Section: Introductionmentioning

confidence: 99%

Quality-adaptive media streaming by priority drop

Krasic¹,

Walpole²,

Feng³

2003

Proceedings of the 13th International Workshop on Network and Operating Systems Support for Digital Audio and Video - NOSSDAV

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This paper presents a general design strategy for streaming media applications in best effort computing and networking environments. Our target application is video on demand using personal computers and the Internet. In this scenario, where resource reservations and admission control mechanisms are not generally available, effective streaming must be able to adapt in a responsive and graceful manner. The design strategy we propose is based on a single simple idea, priority data dropping, or priority drop for short. We evaluate the efficacy of priority drop as an adaptation tool in the video and networking domains. We show how common video compression formats can be extended to support priority drop, thereby becoming streaming friendly. In particular, we demonstrate that priority-drop video allows adaptation over a wide range of rates and with fine granularity, and the adaptation is tailorable through declarative adaptationpolicy specifications. Our technical contribution with respect to video is to show how to express adaptation policies and how to do priority-mapping, an automatic translation from adaptation policies to priority assignments on the basic units of video. For the networking domain, we present priority-progress streaming, a real-time best-effort streaming protocol. We have implemented and released a prototype video streaming system that incorporates prioritydrop video, priority mapping, and priority-progress streaming. The system has the following advantages: it maintains timeliness of the stream in the face of rate fluctuations in the network, it attempts to utilize available bandwidth fully so as to maximize the average video quality, it starts video display quickly after the user initiates the stream, and it limits the number of quality changes that occur. In summary, we will show that priority-drop is very effective: a single video source can be streamed across a wide range of network bandwidths, on networks saturated with competing *

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“…[7,3,1]. We have reflected this in our proposal for PB-RPM by assuming a model (referred to as a presentation quality-based control model) which organizes the cooperation of the following processes according to a producer/consumer concept ( Figure 1).…”

Section: A Model For Pb-rpmmentioning

confidence: 99%