Dynamic network kriging

Ketan Rajawat, Emiliano Dall'Anese, Georgios B Giannakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Path delays in IP networks are important metrics, required by network operators for assessment, planning, and fault diagnosis. Monitoring delays of all source-destination pairs in a large network is however challenging and wasteful of resources. The present paper develops a spatio-temporal prediction approach to track and predict network-wide path delays using measurements on only a few paths. The proposed algorithm uses a space-time Kalman filter that exploits both topological as well as historical data. The resulting predictor is optimal in the class of linear predictors, and outperforms competing alternatives on real-world datasets.

Original languageEnglish (US)
Title of host publication2012 IEEE Statistical Signal Processing Workshop, SSP 2012
Pages121-124
Number of pages4
DOIs
StatePublished - Nov 6 2012
Event2012 IEEE Statistical Signal Processing Workshop, SSP 2012 - Ann Arbor, MI, United States
Duration: Aug 5 2012Aug 8 2012

Publication series

Name2012 IEEE Statistical Signal Processing Workshop, SSP 2012

Other

Other2012 IEEE Statistical Signal Processing Workshop, SSP 2012
CountryUnited States
CityAnn Arbor, MI
Period8/5/128/8/12

Keywords

  • Network kriging
  • kriged Kalman filter
  • latency prediction

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