Traffic prediction of wireless networks attracted many researchers and practitioners during
the past decades. However, wireless traffic frequently exhibits strong nonlinearities and …

We explore the nature of traffic in data centers, designed to support the mining of massive
data sets. We instrument the servers to collect socket-level logs, with negligible performance …

The modeling and analysis of computer communications networks give rise to a variety of
interesting statistical problems. This chapter focuses on network tomography, a term used to …

Network traffic prediction aims at predicting the subsequent network traffic by using the
previous network traffic data. This can serve as a proactive approach for network …

Quantum networks build on entanglement and quantum measurement to achieve tasks that
are beyond the reach of classical systems. Using quantum effects, we can detect the …

This paper presents a new publicly available dataset from GÉANT, the European Research
and Educational Network. This dataset consists of traffic matrices built using full IGP routing …

Many basic network engineering tasks (eg, traffic engineering, capacity planning, anomaly
detection) rely heavily on the availability and accuracy of traffic matrices. However, in …

Despite advances in measurement technology, it is still challenging to reliably compile large-
scale network datasets. For example, because of flaws in the measurement systems or …

Intelligent Internet of Things (IIoT) is comprised of various wireless and wired networks for
industrial applications, which makes it complex and heterogeneous. The openness of IIoT …

In this work we develop an approach for anomaly detection for large scale networks such as
that of an enterprize or an ISP. The traffic patterns we focus on for analysis are that of a …