DocumentCode :
2976569
Title :
Collaborative strategy learning for distributed network self-configuring
Author :
Mbaye, Maïssa ; Krief, Francine ; Soldano, Henry
Author_Institution :
LaBRI, Univ. de Bordeaux, Talence, France
fYear :
2009
fDate :
3-6 Nov. 2009
Firstpage :
1
Lastpage :
8
Abstract :
Self-configuration is one of the most important functions of autonomic networks because it determines optimal use of resources during network´s operation. However, this task is very complex as it must be performed according to service contracts between users and operators, network´s infrastructure and workload. Knowledge Plane is a recently proposed concept to address this complexity by using cognitive tools (learning and reasoning). In this paper, we propose a Knowledge Plane including a distributed and collaborative machine learning method based on inductive logic programming (ILP). The main objective is to achieve distributed self-configuring by learning collaboratively best configuration strategies. We apply it in a practical context (DiffServ) and evaluate effects of this proposal on network´s performances and occupation rate.
Keywords :
cognitive systems; fault tolerant computing; inductive logic programming; learning (artificial intelligence); ILP; autonomic computing; cognitive tools; collaborative machine learning method; distributed network self-configuring; inductive logic programming; knowledge plane; network performances; Collaboration; Collaborative work; Computer architecture; Contracts; Diffserv networks; Knowledge management; Learning systems; Logic; Machine learning; Proposals;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications and Networking, 2009. ComNet 2009. First International Conference on
Conference_Location :
Hammamet
Print_ISBN :
978-1-4244-5134-0
Electronic_ISBN :
978-1-4244-5135-7
Type :
conf
DOI :
10.1109/COMNET.2009.5373555
Filename :
5373555
Link To Document :
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