DocumentCode :
2491339
Title :
Reconstruction mechanism based on distributed intelligent agents for network management
Author :
Li, Hang ; Meng, Lei
Author_Institution :
Shenyang Normal Univ., Shenyang
fYear :
2008
fDate :
25-27 June 2008
Firstpage :
5143
Lastpage :
5147
Abstract :
In order to promote the reliability of network management, a fault tolerant reconstruction mechanism based on distributed intelligent agents is proposed. In a centralized management domain, domain manager is the most important node. So there are a number of distributed intelligent agents that own part or entire function of domain manager as management redundancies. Through the redundancies, it is assured once the domain manager is in invalidate state, the distributed intelligent agents elect the best management ability agent to replace primary manager and reconstructed management domain. This paper puts forward a two-phase fault tolerance reconstruction algorithm with the ability of fault tolerance. Besides, it also gives the formal description of the algorithm and the complex analysis, as well as illustrating the advantage of this algorithm. Moreover, this paper also explains the entity structure of distributed agents.
Keywords :
computer network management; computer network reliability; fault tolerant computing; multi-agent systems; centralized management domain; distributed intelligent agents; fault tolerant reconstruction mechanism; network management; network management reliability; Algorithm design and analysis; Automation; Fault tolerance; Fault tolerant systems; Intelligent agent; Intelligent control; Large-scale systems; Nominations and elections; Reconstruction algorithms; Redundancy; distributed intelligent agent; fault-tolerant; network management; reconstruction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
Type :
conf
DOI :
10.1109/WCICA.2008.4593766
Filename :
4593766
Link To Document :
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