Adaptive scheduling using the revenue-based weighted round robin

Alexander Sayenko, Timo Hämäläinen, Jyrki Joutsensalo, Pertti Raatikainen

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    5 Citations (Scopus)

    Abstract

    This paper presents an adaptive resource allocation model that is based on the WRR queuing discipline. This model ensures QoS requirements and, at the same time, tries to maximize a service provider's revenue by manipulating weights of the WRR scheduler. The model is flexible in that different network services are grouped into service classes and are given different QoS characteristics. To adjust weights, it is proposed to use the revenue criterion that controls the allocation of free resources. The simulation considers a single node with the implemented model that serves several service classes with different QoS requirements and traffic characteristics. It is shown that the total revenue can be increased due to the allocation of unused resources to more expensive service classes. Furthermore, the adaptive model eliminates the need to find optimal static weight values because they are calculated dynamically.
    Original languageEnglish
    Title of host publicationProceedings, 12th IEEE International Conference on Networks (ICON 2004)
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Pages743-749
    Volume2
    ISBN (Print)0-7803-8783-X
    DOIs
    Publication statusPublished - 2004
    MoE publication typeA4 Article in a conference publication
    Event12th IEEE International Conference on Networks, ICON 2004 - Singapore, Singapore
    Duration: 16 Nov 200419 Nov 2004

    Publication series

    SeriesIEEE International Conference On Networks
    Volume2004
    ISSN1531-2216

    Conference

    Conference12th IEEE International Conference on Networks, ICON 2004
    Country/TerritorySingapore
    CitySingapore
    Period16/11/0419/11/04

    Keywords

    • resource allocation
    • QoS
    • queueing discipline
    • scheduling algorithm

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