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2009 Third IEEE International Conference on Self-Adaptive and Self-Organizing Systems
Self-organizing Bandwidth Sharing in Priority-Based Medium Access
San Francisco, California, USA
September 14-September 18
ISBN: 978-0-7695-3794-8
ASCII Text
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Stefan Wildermann, Tobias Ziermann, Jürgen Teich, "Self-organizing Bandwidth Sharing in Priority-Based Medium Access," Self-Adaptive and Self-Organizing Systems, IEEE International Conference on, pp. 144-153, 2009 Third IEEE International Conference on Self-Adaptive and Self-Organizing Systems, 2009.
 
 
BibTex
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@article{ 10.1109/SASO.2009.18,
author = {Stefan Wildermann and Tobias Ziermann and Jürgen Teich},
title = {Self-organizing Bandwidth Sharing in Priority-Based Medium Access},
journal ={Self-Adaptive and Self-Organizing Systems, IEEE International Conference on},
volume = {0},
year = {2009},
isbn = {978-0-7695-3794-8},
pages = {144-153},
doi = {http://doi.ieeecomputersociety.org/10.1109/SASO.2009.18},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Self-Adaptive and Self-Organizing Systems, IEEE International Conference on
TI - Self-organizing Bandwidth Sharing in Priority-Based Medium Access
SN - 978-0-7695-3794-8
SP144
EP153
A1 - Stefan Wildermann,
A1 - Tobias Ziermann,
A1 - Jürgen Teich,
PY - 2009
KW - Multi-agent Reinforcement learning
KW - Priority-based Medium Access
KW - Game Theory
VL - 0
JA - Self-Adaptive and Self-Organizing Systems, IEEE International Conference on
ER -
 
In this paper, we present an analysis of self-organizing bandwidth sharing in priority-based medium access. For this purpose, the priority-based Access Game is introduced. Analysis shows that a fair distribution of bandwidth cannot be achieved in this game. Therefore, we enhance this game by introducing a constraint that demands a small amount of the overall bandwidth being free. Fair bandwidth sharing is one Nash Equilibrium of this enhanced game, but not a unique one. Based upon this theoretical analysis, a multi-agent reinforcement learning algorithm is proposed, where each agent tries to maximize its success rate for accessing the medium, while avoiding to violate the bandwidth constraint. We experimentally evaluate this mechanism for a system comprised of selfish agents. Experimental results show that the system is able to self-organize itself towards a fair distribution of bandwidth in a totally decentralized way without the need of global information or coordination.
Index Terms:
Multi-agent Reinforcement learning, Priority-based Medium Access, Game Theory
Citation:
Stefan Wildermann, Tobias Ziermann, Jürgen Teich, "Self-organizing Bandwidth Sharing in Priority-Based Medium Access," saso, pp.144-153, 2009 Third IEEE International Conference on Self-Adaptive and Self-Organizing Systems, 2009
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