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Cache architecture for on-demand streaming on the Web

Authors:

Raj Sharman,

Shiva Shankar Ramanna,

Ram Ramesh,

Ram GopalAuthors Info & Claims

ACM Transactions on the Web (TWEB), Volume 1, Issue 3

Pages 13 - es

https://doi.org/10.1145/1281480.1281483

Published: 01 September 2007 Publication History

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Abstract

On-demand streaming from a remote server through best-effort Internet poses several challenges because of network losses and variable delays. The primary technique used to improve the quality of distributed content service is replication. In the context of the Internet, Web caching is the traditional mechanism that is used. In this article we develop a new staged delivery model for a distributed architecture in which video is streamed from remote servers to edge caches where the video is buffered and then streamed to the client through a last-mile connection. The model uses a novel revolving indexed cache buffer management mechanism at the edge cache and employs selective retransmissions of lost packets between the remote and edge cache for a best-effort recovery of the losses. The new Web cache buffer management scheme includes a dynamic adjustment of cache buffer parameters based on network conditions. In addition, performance of buffer management and retransmission policies at the edge cache is modeled and assessed using a probabilistic analysis of the streaming process as well as system simulations. The influence of different endogenous control parameters on the quality of stream received by the client is studied. Calibration curves on the QoS metrics for different network conditions have been obtained using simulations. Edge cache management can be done using these calibration curves. ISPs can make use of calibration curves to set the values of the endogenous control parameters for specific QoS in real-time streaming operations based on network conditions. A methodology to benchmark transmission characteristics using real-time traffic data is developed to enable effective decision making on edge cache buffer allocation and management strategies.

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Jevremovic APopovic RZivkovic DVeinovic MShimic G(2011)DMS — Improving Web performance2011 19thTelecommunications Forum (TELFOR) Proceedings of Papers10.1109/TELFOR.2011.6143518(166-169)Online publication date: Nov-2011
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Cache architecture for on-demand streaming on the Web

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Reviews

Reviewer: Fjodor J. Ruzic

This paper discusses new Web caching strategies, analyzes cache performance, and describes how to model the Web cache architecture for video on-demand streaming. The authors clearly distinguish between semi and real on-demand streaming, each of which requires different bandwidth levels. It is worth mentioning that the authors' Web caching architecture consists of two components: a remote-server application and an edge-cache server application. The architecture is modeled and the performance is assessed using probabilistic analysis and system simulations. The authors propose a remote streaming architecture based on real-time streaming protocol (RTSP) channels, where actual video transmission occurs over user datagram protocol (UDP) channels using real-time transport protocols/real-time transport control protocols (RTP)/(RTCP). This way, the streaming session has a persistent connection that connects the remote server and edge cache server. Besides the clear description of each part of this architecture, the authors provide basic performance metrics. The authors created two models. The first one copes with probabilistic performance with two approaches-with and without retransmission, each noting quality of service (QoS) metrics. The second one is a system simulation model. This model copes with various streaming scenarios, and has to evaluate different issues, including: considering the QoS evaluation, with and without retransmission; studying the effects of control parameters on the percentage of useful retransmissions realized at the user side; and obtaining a visible relationship between two QoS simulations that can be used for setting appropriate values for the control parameters in real-world streaming sessions. Based on the system simulation model, the authors stressed the results of their findings. There are three categories of results: the effects of control parameters on QoS, the effects of control parameters on the usefulness of retransmission, and the QoS calibration curves presentation. The conclusion, which accompanies references on Web caching and Internet streaming issues, provides clear insight on the problem, and discusses streaming architecture for pure unicast streaming, using partial caching on edge-cache servers. At the same time, the authors discuss new areas for future research, aiming to provide a qualitative basis for service level agreements in the content services sector. It is certainly interesting reading. It will be a valuable source for those dealing with on-demand video content services over the Internet. Online Computing Reviews Service

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Published In

ACM Transactions on the Web Volume 1, Issue 3

September 2007

145 pages

ISSN:1559-1131

EISSN:1559-114X

DOI:10.1145/1281480

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 2007

Published in TWEB Volume 1, Issue 3

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Cited By

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https://dl.acm.org/doi/10.1007/978-3-319-20804-6_35
Jevremovic APopovic RZivkovic DVeinovic MShimic G(2011)DMS — Improving Web performance2011 19thTelecommunications Forum (TELFOR) Proceedings of Papers10.1109/TELFOR.2011.6143518(166-169)Online publication date: Nov-2011
https://doi.org/10.1109/TELFOR.2011.6143518
Kannammal APadmanabhan RIyengar N(2010)Web Cache Consistency Maintenance Through AgentsProceedings of the 2010 Second International Conference on Communication Software and Networks10.1109/ICCSN.2010.84(329-333)Online publication date: 26-Feb-2010
https://dl.acm.org/doi/10.1109/ICCSN.2010.84
Bica IGhita STogan M(2010)An IP multicast - HTTP Gateway for reliable streaming in heterogeneous networks2010 8th International Conference on Communications10.1109/ICCOMM.2010.5509058(389-392)Online publication date: Jun-2010
https://doi.org/10.1109/ICCOMM.2010.5509058
Du AGeng XGopal RRamesh RWhinston A(2008)Capacity Provision NetworksInformation Systems Research10.1287/isre.1070.014519:2(144-160)Online publication date: 1-Jun-2008
https://dl.acm.org/doi/10.1287/isre.1070.0145

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