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Journal of Network and Systems Management

Erschienen in:

14.09.2016

Performance Analysis of Network Traffic Predictors in the Cloud

verfasst von: Bruno L. Dalmazo, João P. Vilela, Marilia Curado

Erschienen in: Journal of Network and Systems Management | Ausgabe 2/2017

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Abstract

Predicting the inherent traffic behaviour of a network is an essential task, which can be used for various purposes, such as monitoring and managing the network’s infrastructure. However, the recent surge of dynamic environments, such as Internet of Things and Cloud Computing have hampered this task. This means that the traffic on these networks is even more complex, displaying a nonlinear behaviour with specific aperiodic characteristics during daily operation. Traditional network traffic predictors are usually based on large historical data bases which are used to train algorithms. This may not be suitable for these highly volatile environments, where the strength of the force exerted in the interaction between past and current values may change quickly with time. In light of this, a taxonomy for network traffic prediction models, including the review of state of the art, is presented here. In addition, an analysis mechanism, focused on providing a standardized approach for evaluating the best candidate predictor models for these environments, is proposed. These contributions favour the analysis of the efficacy and efficiency of network traffic prediction among several prediction models in terms of accuracy, historical dependency, running time and computational overhead. An evaluation of several prediction mechanisms is performed by assessing the Normalized Mean Square Error and Mean Absolute Percent Error of the values predicted by using traces taken from two real case studies in cloud computing.

Vorheriger Artikel Robustness Comparison of 15 Real Telecommunication Networks: Structural and Centrality Measurements

Nächster Artikel A Survey on Software Defined Networking: Architecture for Next Generation Network

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Titel: Performance Analysis of Network Traffic Predictors in the Cloud
verfasst von: Bruno L. Dalmazo
João P. Vilela
Marilia Curado
Publikationsdatum: 14.09.2016
Verlag: Springer US
Erschienen in: Journal of Network and Systems Management / Ausgabe 2/2017
Print ISSN: 1064-7570
Elektronische ISSN: 1573-7705
DOI: https://doi.org/10.1007/s10922-016-9392-x

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