A Variant betweenness Centrality Approach towards Distributed Network Monitoring

As the development of Internet thrives, the network management has to be taken a serious look. This paper faces the dilemma of putting more monitors into the system and maintains the original settings at the same time. We research the adding mechanism and present a new algorithm for finding the crit...

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Published in2011 Fourth International Symposium on Parallel Architectures, Algorithms and Programming pp. 340 - 344
Main Authors Peng Ou, Zhishu Li
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2011
Subjects
Online AccessGet full text
ISBN1457718081
9781457718083
ISSN2168-3034
DOI10.1109/PAAP.2011.53

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Abstract As the development of Internet thrives, the network management has to be taken a serious look. This paper faces the dilemma of putting more monitors into the system and maintains the original settings at the same time. We research the adding mechanism and present a new algorithm for finding the critical locations for additional deployment in the network, in the context of traffic estimation with link weight change method. The algorithm is based on Apriori search method that combines with the link weight change algorithm, then tested with Between ness Centrality to form the candidate snapshots. We also develop the greedy algorithm with Group Between ness Centrality(GBC) involved for the purpose of comparing. The result shows that the new algorithm need less additional monitors than greedy algorithm.
AbstractList As the development of Internet thrives, the network management has to be taken a serious look. This paper faces the dilemma of putting more monitors into the system and maintains the original settings at the same time. We research the adding mechanism and present a new algorithm for finding the critical locations for additional deployment in the network, in the context of traffic estimation with link weight change method. The algorithm is based on Apriori search method that combines with the link weight change algorithm, then tested with Between ness Centrality to form the candidate snapshots. We also develop the greedy algorithm with Group Between ness Centrality(GBC) involved for the purpose of comparing. The result shows that the new algorithm need less additional monitors than greedy algorithm.
Author Zhishu Li
Peng Ou
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Snippet As the development of Internet thrives, the network management has to be taken a serious look. This paper faces the dilemma of putting more monitors into the...
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StartPage 340
SubjectTerms Algorithm design and analysis
Estimation
Greedy algorithms
Inference algorithms
Measurement
Monitoring
Routing
Title A Variant betweenness Centrality Approach towards Distributed Network Monitoring
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