Scalable server and storage architectures for video streaming

Du, D.H.C.; Lee, Yen-Jen

doi:10.1109/mmcs.1999.779121

Cited by 7 publications

(6 citation statements)

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“…The disk scheduling algorithms and admission control algorithms determine how data requests are performed over the disks and how to accommodating as more clients as possible with limited resource, while not violating the real-time requirements of admitted clients. So far as we know, there have been quite a few literature documenting the development of storage system design [36] [29] [71], either for a single machine or a distributed server, but few comprehensive discussion of clustered multimedia server architecture can be found. This paper survey over twenty server systems and develop a taxonomy for the server architecture.…”

Section: Real-time Servicementioning

confidence: 99%

“…One weakness of this architecture is that a part of application software is required to be bounded with the Storage Servers in addition to their responsibility of data storage and retrieval. For some storage architectures like SAN (Storage Area Network) [29]or NAS (Network Attached Storage) [38], in which the storage nodes are composed of a variety of heterogeneous storage devices such as disk arrays, tape libraries and optical storage arrays, this is sometimes unfeasible due to the limited software supports by these devices.…”

Section: Direct Access Modementioning

confidence: 99%

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Clustered Multimedia Servers: Architectures and Storage Systems

Tan

Jin

2003

Annual Review of Scalable Computing

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This paper presents an overview of the recent advances on the design of clustered multimedia servers. It is focused on the following aspects: server architecture, media data organization, real-time stream scheduling and admission control algorithms. For the architecture, we give a taxonomy regarding the various structures of cluster components, and survey over 20 existing server systems, either from the laboratories or the industry. We then examine the data organization methods employed in multimedia servers, which shape the system behavior in many aspects. To reveal the essentials of multimedia service, we take a closer look at the real-time scheduling techniques for streaming data. The admission control issue is finally discussed as an indispensable component for both efficient resource utilization and guaranteed QoS for clients.

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Section: Real-time Servicementioning

confidence: 99%

Section: Direct Access Modementioning

confidence: 99%

Clustered Multimedia Servers: Architectures and Storage Systems

Tan

Jin

2003

Annual Review of Scalable Computing

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“…17) [16], [28]. An SAN can provide high-speed data pipes between storage devices and hosts at far greater distances than conventional host-attached small-computer-systems-interface (SCSI).…”

Section: B Storage Systemmentioning

confidence: 99%

Streaming video over the Internet: approaches and directions

Hou

Zhu

et al. 2001

IEEE Trans. Circuits Syst. Video Technol.

486

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Abstract-Due to the explosive growth of the Internet and increasing demand for multimedia information on the web, streaming video over the Internet has received tremendous attention from academia and industry. Transmission of real-time video typically has bandwidth, delay, and loss requirements. However, the current best-effort Internet does not offer any quality of service (QoS) guarantees to streaming video. Furthermore, for video multicast, it is difficult to achieve both efficiency and flexibility. Thus, Internet streaming video poses many challenges. To address these challenges, extensive research has been conducted. This special issue is aimed at dissemination of the contributions in the field of streaming video over the Internet. To introduce this special issue with the necessary background and provide an integral view on this field, we cover six key areas of streaming video. Specifically, we cover video compression, application-layer QoS control, continuous media distribution services, streaming servers, media synchronization mechanisms, and protocols for streaming media. For each area, we address the particular issues and review major approaches and mechanisms. We also discuss the tradeoffs of the approaches and point out future research directions.

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“…The large amount of network traffics and the high performance computing ability are inevitable to support the QoS streams [1,2,3]. However, since the wireless network has low bandwidth channels and many * This research was financially supported by the Ministry of Commerce, Industry and Energy (MOCIE) and Korea Industrial Technology Foundation (KOTEF) through the Human Resource Training Project for Regional Innovation.…”

Section: Introductionmentioning

confidence: 99%

“…The transcoding server performs the transcoding to original MPEG video and also sustains the streaming service to the corresponding client. In particular, to provide QoS for clients, it is inevitable to guarantee streaming media without ceasing and jittering phenomena [3,4,5,6,7].…”

Section: Introductionmentioning

confidence: 99%

Load Distribution Method and Admission control for Streaming Media QoS in Distributed Transcoding Servers

Heo

Lim

Seo

et al. 2007

2007 International Conference on Computational Science and Its Applications (ICCSA 2007)

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The recent advance in wireless network technologies has enabled the streaming media service on the mobile devices such as PDAs and cellular phones. Since the wireless network has low bandwidth channels and mobile devices are actually composed of limited hardware specifications, the transcoding technology is needed to adapt streaming media to the given mobile devices. When large scale mobile clients demand the streaming service, load distribution Methods among transcoding servers highly impact on the total number of QoS streams. In this paper, the resource weighted load distribution Method is proposed for the fair load distribution and the more scalable performance in distributed transcoding servers. Our proposed Method is based on the weight of resources consumed for transcoding to classified client grades and the maximum number of QoS streams actually measured in transcoding servers. The proposed policy is implemented on distributed transcoding system. In experiments, we evaluate its fair load distribution and scalable performance according to the increase of transcoding servers.

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Scalable server and storage architectures for video streaming

Cited by 7 publications

References 0 publications

Clustered Multimedia Servers: Architectures and Storage Systems

Clustered Multimedia Servers: Architectures and Storage Systems

Streaming video over the Internet: approaches and directions

Load Distribution Method and Admission control for Streaming Media QoS in Distributed Transcoding Servers

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