Abstract | ||
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Many network management actions need a simultaneous consideration of several elements’ state. This is becoming an even more complex matter with the advent of reconfigurable deployments, where scaling functions up can prevent performance bottlenecks. Therefore, fine-grained detection of significant burdens arises as a cornerstone to optimize their monitoring and operation. We present advanced distributed passive retrieval of information, and statistical multi-point analysis (
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), a passive monitoring system intended to fit models for network delay measurements with clustering elements to improve representation of central and extreme behaviors. As distinguishing features, it relies on cost-effective multi-point round-trip time (RTT) passive network measurements, and is able to select a suitable parametric model optimizing the trade-off between fitting and complexity.
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can correlate records collected from several vantage points and detect where performance issues are most likely to appear; adjust alarms in terms of the probability of events; and adapt its behavior to dynamic network conditions while presenting a fair identification of anomalous situations. We evaluate
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with experiments both in virtual environments and with real-world data to provide evidences of its applicability and capabilities to represent network elements’ delay. |
Year | DOI | Venue |
---|---|---|
2019 | 10.1109/TNSM.2019.2924812 | IEEE Transactions on Network and Service Management |
Keywords | Field | DocType |
network monitoring,network delay,round-trip time,probability,passive measurements,performance management,pro-active management | Dynamic network analysis,Network delay,Passive monitoring,Computer science,Network element,Round-trip delay time,Network monitoring,Network management,Cluster analysis,Distributed computing | Journal |
Volume | Issue | ISSN |
16 | 3 | 1932-4537 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Daniel Perdices | 1 | 0 | 1.01 |
David Muelas | 2 | 32 | 6.70 |
Iria Prieto | 3 | 0 | 0.34 |
Luis de Pedro | 4 | 2 | 1.40 |
Jorge E. López de Vergara | 5 | 187 | 26.98 |