Metro-Haul’ers Win Best Student Paper Award at CNSM 2018
Well done to Daniel Perdices and his co-authors: David Muelas, Luis de Pedro, Jorge E. L´opez de Vergara; for their award-winning paper “Network Performance Monitoring with Flexible Models of Multi-Point Passive Measurements”. This paper was published the 14th International Conference on Network and Service Management 2018 – http://cnsm-conf.org/2018/.
Their award-winning paper highlights the many concurrent management actions required for operation of network infrastructure. This is particularly critical in the case of reconfigurable deployments, such as Virtual Functions or Software-Defined Networks, to scale the affected equipment up and prevent performance bottlenecks. The paper provides an overview of dPRISMA (distributed Passive Retrieval of Information, and Statistical Multipoint Analysis), a passive monitoring system intended to fit statistical models for network measurements and raise alarms in the case of extreme behaviors.
The dPRISMA platform relies on cost-effective multi-point network measurements and is able to select a suitable parametric model optimizing the trade-off between fitting and complexity. Therefore, it can (i) correlate records collected from several vantage points and detect where performance issues are most likely to appear; (ii) adjust alarms in terms of the probability of events; and (iii) adapt its behavior to dynamic network conditions while presenting a fair identification of anomalous situations. The paper evaluates dPRISMA with experiments both in virtual environments and with real-world data to provide evidences of its applicability.
The Operation of dPRISMA is highlighted in the figure above. The red arrows represent a sample connection traversing the three monitored points of the network, distinguishing the different RTT components that are estimated to detect possible bottlenecks.
The experimental dPRISMA platform is available as open source code and may be found on GitHub: https://github.com/hpcn-uam/dprisma.
