By developing cities and increasing population, smart transportation becomes an essential
component of modern societies. Extensive research activities using machine learning …

This article presents an algorithm to detect outliers in seasonal, univariate network traffic
data using Gaussian Mixture Models (GMMs). Additionally we show that this methodology …

The evolving trends of mobility, cloud computing and collaboration have blurred the
perimeter separating corporate networks from the wider world. These new tools and …

In this paper, we present a robust spatiotemporal statistical methodology that is capable of
accurately forecasting traffic in the flood-prone area of the Mandolossa in the Province of …

While urbanization brings economic and social benefits, it also causes water pollution and
other environmental ecological problems. This paper provides a theoretical framework to …

Various statistical analysis methods are studied for years to extract accurate trends of
network traffic and predict the future load mainly to allocate required resources. Besides …

Web performance anomalies (eg time periods when metrics like page load time are
abnormally high) have significant impact on user experience and revenues of web service …

Accurate Internet traffic predictions can provide support to network operators for applications
such as traffic engineering, bandwidth allocation, anomaly detection, etc. We apply and …

This article examines the issue of forecasting the time series of server systems and suggests
applying the triple exponential smoothing model to solve this problem. It presents a …

As the importance of the Internet increases, developing technologies for data transmission at
higher bit rates became as important as challenging. Optical Transport Networks (OTN) …