Bañares, José Ángel, Rana, Omer Farooq ![]() |
Abstract
With the increasing availability of streaming applications from mobile devices to dedicated sensors, understanding how such streaming content can be processed within some time threshold remains an important requirement. We investigate how a computational infrastructure responds to such streaming content based on the revenue per stream – taking account of the price paid to process each stream, the penalty per stream if the pre-agreed throughput rate is not met, and the cost of resource provisioning within the infrastructure. We use a token-bucket based rate adaptation strategy to limit the data injection rate of each data stream, along with the use of a shared token-bucket to enable better allocation of computational resource to each stream. We demonstrate how the shared token-bucket based approach can enhance the performance of a particular class of applications, whilst still maintaining a minimal quality of service for all streams entering the system.
Item Type: | Conference or Workshop Item (Paper) |
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Date Type: | Publication |
Status: | Published |
Schools: | Computer Science & Informatics |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Publisher: | Springer |
ISBN: | 9783319024134 |
ISSN: | 0302-9743 |
Last Modified: | 25 Oct 2022 08:02 |
URI: | https://orca.cardiff.ac.uk/id/eprint/51170 |
Citation Data
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