Journal
COMPUTER COMMUNICATIONS
Volume 150, Issue -, Pages 393-404Publisher
ELSEVIER
DOI: 10.1016/j.comcom.2019.11.052
Keywords
Converged fixed-mobile networks; Real-time KPI estimation; Shared medium modeling
Categories
Funding
- European Commission [761727]
- AEI/FEDER TWINS project, Spain [TEC2017-90097-R]
- Catalan Institution for Research and Advanced Studies (ICREA), Spain
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The independent operation of mobile and fixed network segments is one of the main barriers that prevents improving network performance while reducing capital expenditures coming from overprovisioning. In particular, a coordinated dynamic network operation of both network segments is essential to guarantee end-to-end Key Performance Indicators (KPI), on which new network services rely on. To achieve such dynamic operation, accurate estimation of end-to-end KPIs is needed to trigger network reconfiguration before performance degrades. In this paper, we present a methodology to achieve an accurate, scalable, and predictive estimation of end-to-end KPIs with sub-second granularity near real-time in converged fixed-mobile networks. Specifically, we extend our CURSA-SQ methodology for mobile network traffic analysis, to enable converged fixed-mobile network operation. CURSA-SQ combines simulation and machine learning fueled with real network monitoring data. Numerical results validate the accuracy, robustness, and usability of the proposed CURSA-SQ methodology for converged fixed-mobile network scenarios.
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