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First International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2007)
A Weighted Voting Mechanism for Action Selection Problem in Self-Adaptive Software
Cambridge, Massachussets
July 09-July 11
ISBN: 0-7695-2906-2
ASCII Text
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Mazeiar Salehie, Ladan Tahvildari, "A Weighted Voting Mechanism for Action Selection Problem in Self-Adaptive Software," Self-Adaptive and Self-Organizing Systems, IEEE International Conference on, pp. 328-331, First International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2007), 2007.
 
 
BibTex
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@article{ 10.1109/SASO.2007.4,
author = {Mazeiar Salehie and Ladan Tahvildari},
title = {A Weighted Voting Mechanism for Action Selection Problem in Self-Adaptive Software},
journal ={Self-Adaptive and Self-Organizing Systems, IEEE International Conference on},
volume = {0},
year = {2007},
isbn = {0-7695-2906-2},
pages = {328-331},
doi = {http://doi.ieeecomputersociety.org/10.1109/SASO.2007.4},
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 - A Weighted Voting Mechanism for Action Selection Problem in Self-Adaptive Software
SN - 0-7695-2906-2
SP328
EP331
A1 - Mazeiar Salehie,
A1 - Ladan Tahvildari,
PY - 2007
VL - 0
JA - Self-Adaptive and Self-Organizing Systems, IEEE International Conference on
ER -
 
Mazeiar Salehie, University of Waterloo,ON, Canada
Ladan Tahvildari, University of Waterloo,ON, Canada
Self-adaptive software is a closed-loop system which aims at adjusting itself in response to changes at runtime. Such a system is required to monitor domain events, detect significant changes, decide how to react, and act in order to execute the decisions. This paper focuses on the deciding process particularly for application-level adaptation actions. For this purpose, a weighted voting mechanism has been proposed which makes decisions based on a Goal-Action- Attribute Model (GAAM). The decision-making algorithm traverses GAAM, determines activated goals and feasible actions for voting, and ultimately selects an action as the social choice. The proposed mechanism and GAAM are evaluated within a simulated model of a news web site.
Citation:
Mazeiar Salehie, Ladan Tahvildari, "A Weighted Voting Mechanism for Action Selection Problem in Self-Adaptive Software," saso, pp.328-331, First International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2007), 2007
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