Paper Info
Title
Facing Network Management Challenges with Functional Data Analysis: Techniques & Opportunities.
Abstract
Current fixed and mobile networks’ behavior is rapidly changing, which calls for flexible monitoring approaches to avoid loosing track with such a fast evolutionary pace. Due to the many challenges that this scenario is posing to network managers, we propose the exploration of Functional Data Analysis (FDA) techniques as a mean to easily deal with network management and analysis issues. Specifically, we describe and evaluate several FDA methods with applications to network measurement preprocessing and clustering, bandwidth allocation, and anomaly and outlier detection. Our work focuses on how these FDA-based tools serve to improve the outcomes of traffic data mining and analysis, providing easy-to-understand and comprehensive outputs for network managers. We present the results that we have obtained from real case studies in the Spanish Academic network using throughput time series, comparing them with other alternatives of the state of the art. With this com- parative, we have qualitatively and quantitatively evaluated the advantages of FDA-methods in the networking area.
Year
DOI
Venue
2017
https://doi.org/10.1007/s11036-016-0733-5
MONET
Keywords
Field
DocType
Network management,Functional data analysis,Traffic modeling,Baselines,Capacity planning,Anomaly detection
Functional data analysis,Data science,Anomaly detection,Data mining,Pace,Bandwidth allocation,Computer science,Capacity planning,Throughput,Cluster analysis,Network management,Distributed computing
Journal
Volume
Issue
ISSN
22
6
1383-469X
Citations 
PageRank 
References 
2
0.41
21
Authors
5
Name
Order
Citations
PageRank
David Muelas1326.70
Jorge E. López de Vergara218726.98
José R. Berrendero3172.85
Javier Ramos4488.30
Javier Aracil521342.23