Premium
Digital signature to help network management using flow analysis
Author(s) -
Proença Mario Lemes,
Fernandes Gilberto,
Carvalho Luiz F.,
Assis Marcos V. O.,
Rodrigues Joel J. P. C.
Publication year - 2015
Publication title -
international journal of network management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.373
H-Index - 28
eISSN - 1099-1190
pISSN - 1055-7148
DOI - 10.1002/nem.1892
Subject(s) - computer science , ant colony optimization algorithms , network packet , heuristic , traffic flow (computer networking) , traffic analysis , data mining , measure (data warehouse) , metaheuristic , adaptability , principal component analysis , flow (mathematics) , flow network , signature (topology) , algorithm , artificial intelligence , mathematical optimization , computer network , mathematics , ecology , geometry , biology
Summary Because of constant growth in proportion and complexity of networks, flow analysis has become an indispensable tool for network management mechanisms. Through this resource, a traffic characterization, called digital signature of network segment using flow analysis (DSNSF), is accomplished. The models used for this purpose are the ant colony optimization metaheuristic, the Holt–Winters forecasting method and the statistical procedure, principal component analysis. The obtained DSNSF by each model is compared with the actual traffic of packets and bits and then subjected to specific evaluations in order to measure its accuracy. The experimental results show that the three methods could achieve good correlation indices and low normalized mean square error values between the DSNSF curve and the real traffic movement, indicating a good adaptability and efficiency in characterizing a network traffic segment. Copyright © 2015 John Wiley & Sons, Ltd.