DocumentCode
580430
Title
Performance evaluation of a distributed and probabilistic network monitoring approach
Author
Steinert, R. ; Gillblad, D.
Author_Institution
Ind. Applic. & Methods Lab. (IAM), Swedish Inst. of Comput. Sci. (SICS), Kista, Sweden
fYear
2012
fDate
22-26 Oct. 2012
Firstpage
242
Lastpage
246
Abstract
We investigate the effects of employing a probabilistic fault detection approach relative the performance of a deterministic network monitoring method. The approach has its foundation in probabilistic network management, in which performance limits and thresholds are specified in terms of e.g. probabilities or belief values. When combined with adaptive mechanisms, probabilistic approaches can potentially offer improved controllability, adaptivity and reliability, compared to deterministic monitoring methods. Results from synthetically generated and real network QoS measurements indicate that the probabilistic approach generally can perform at least as good as a deterministic algorithm, with a higher degree of predictable performance and resource-efficiency. Due to the stochastic nature of the algorithm, worse performance than expected is sometimes observed. Nevertheless, the results give additional support to some of the practical benefits expected in using probabilistic approaches for network management purposes.
Keywords
controllability; fault diagnosis; performance evaluation; adaptive mechanism; adaptivity; controllability; deterministic algorithm; deterministic network monitoring; performance evaluation; probabilistic fault detection; probabilistic network management; probabilistic network monitoring; real network QoS measurement; reliability; Delay; Fault detection; Monitoring; Phase frequency detector; Prediction algorithms; Probabilistic logic; Probes; adaptive fault detection; network monitoring; probabilistic network management;
fLanguage
English
Publisher
ieee
Conference_Titel
Network and service management (cnsm), 2012 8th international conference and 2012 workshop on systems virtualiztion management (svm)
Conference_Location
Las Vegas, NV
Print_ISBN
978-1-4673-3134-0
Electronic_ISBN
978-3-901882-48-7
Type
conf
Filename
6380023
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