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
CountrySingapore
CitySingapore
Period16/11/0419/11/04

Keywords

  • resource allocation
  • QoS
  • queueing discipline
  • scheduling algorithm

Fingerprint Dive into the research topics of 'Adaptive scheduling using the revenue-based weighted round robin'. Together they form a unique fingerprint.

  • Cite this

    Sayenko, A., Hämäläinen, T., Joutsensalo, J., & Raatikainen, P. (2004). Adaptive scheduling using the revenue-based weighted round robin. In Proceedings, 12th IEEE International Conference on Networks (ICON 2004) (Vol. 2, pp. 743-749). IEEE Institute of Electrical and Electronic Engineers. IEEE International Conference On Networks, Vol.. 2004 https://doi.org/10.1109/ICON.2004.1409276