Paper
10 December 2001 Time-domain modeling of batching under user interaction and dynamic adaptive piggybacking schemes
Wang Ke, Prithwish Basu, Thomas D.C. Little
Author Affiliations +
Proceedings Volume 4673, Multimedia Computing and Networking 2002; (2001) https://doi.org/10.1117/12.449975
Event: Electronic Imaging, 2002, San Jose, California, United States
Abstract
Provision of Video-on-Demand (VoD) services may require high network bandwidth and server capacity for sustained periods of time. Aggregation schemes can be used to increase the supported customer population under the constraints of these resources, but due to system behavioral complexity, these schemes have been difficult to model in the large scale. We present in this paper a time-domain analysis modeling technique that yields satisfactory performance estimation results. We show that our analysis is analogous to finding the time response of linear systems using the well known convolution theorem. We model two aggregation schemes using this technique: (1) batching by time-out and (2) adaptive piggybacking employing Snapshot-RSMA. Both schemes are server based aggregation schemes, and their importance increases as pervasive computing, with possibly many capacity-limited devices (such as PDAs) connected as potential recipients of streaming VoD, becomes closer to reality. Since such schemes do not assume any end client capacity requirements, they are the logical candidates for enabling efficient VoD service in a pervasive computing environment. We delineate the requirements of the VoD system under which this modeling technique can be employed and also propose a sampling methodology which gives good estimation results when modeling becomes too complex mathematically.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wang Ke, Prithwish Basu, and Thomas D.C. Little "Time-domain modeling of batching under user interaction and dynamic adaptive piggybacking schemes", Proc. SPIE 4673, Multimedia Computing and Networking 2002, (10 December 2001); https://doi.org/10.1117/12.449975
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Cited by 2 scholarly publications.
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KEYWORDS
Video

Mathematical modeling

Systems modeling

Computer simulations

Convolution

Process modeling

Computing systems

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