On the Modeling of Multi-Point RTT Passive Measurements for Network Delay Monitoring

• Published in: IEEE eTransactions on network and service management Vol. 16; no. 3; pp. 1157 - 1169
• Main Authors: Perdices, Daniel, Muelas, David, Prieto, Iria, de Pedro, Luis, Lopez de Vergara, Jorge E.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Clustering; Complexity; Complexity theory; Computational modeling; Data models; Delay; Delays; Information retrieval; Monitoring; network delay; network monitoring; Optimization; passive measurements; performance management; pro-active management; probability; round-trip time; Statistical analysis; Trip generation; Virtual environments; Weibull distribution
• ISSN: 1932-4537; 1932-4537
• DOI: 10.1109/TNSM.2019.2924812

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 ( AdPRISMA ), 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. AdPRISMA 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 AdPRISMA with experiments both in virtual environments and with real-world data to provide evidences of its applicability and capabilities to represent network elements' delay.