@inproceedings{c4a422f732ba43fe827dc8d9ac0a60fd,
title = "Adaptive scheduling using the revenue-based weighted round robin",
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.",
keywords = "resource allocation, QoS, queueing discipline, scheduling algorithm",
author = "Alexander Sayenko and Timo H{\"a}m{\"a}l{\"a}inen and Jyrki Joutsensalo and Pertti Raatikainen",
note = "Project code: T2SU00019; 12th IEEE International Conference on Networks, ICON 2004 ; Conference date: 16-11-2004 Through 19-11-2004",
year = "2004",
doi = "10.1109/ICON.2004.1409276",
language = "English",
isbn = "978-0-7803-8783-6",
volume = "2",
series = "IEEE International Conference On Networks",
publisher = "IEEE Institute of Electrical and Electronic Engineers",
pages = "743--749",
booktitle = "2004 IEEE 12th International Conference on Networks (ICON 2004)",
address = "United States",
}