Since the seminal study of Leland, Taqqu, Willinger, and Wilson, which set the groundwork
for considering self‐similarity an important notion in the understanding of network traffic …

Traffic dynamics on complex networks are intriguing in recent years due to their practical
implications in real communication networks. In this survey, we give a brief review of studies …

Network function virtualization (NFV) is a promising technology to decouple the network
functions from dedicated hardware elements, leading to the significant cost reduction in …

Long-memory, or more generally fractal, processes are known to play an important role in
many scientific disciplines and applied fields such as physics, geophysics, hydrology …

This comprehensive text gives an interesting and useful blend of the mathematical,
probabilistic and statistical tools used in heavy-tail analysis. Heavy tails are characteristic of …

The theoretical and empirical econometric literatures on long memory and regime switching
have evolved largely independently, as the phenomena appear distinct. We argue, in …

A number of empirical studies of traffic measurements from a variety of working packet
networks have demonstrated that actual network traffic is self-similar or long-range …

Излагаются основные положения, модели и алгоритмы, используемые для оценки
характеристик передачи трафика сервисов реального времени и данных в сетях и …

The recent discovery of scaling phenomena in modern communication networks involving
self-similarity or fractals and power-law or heavy-tailed distributions is yet another realization …

We propose a routing strategy to improve the transportation efficiency on complex networks.
Instead of using the routing strategy for shortest path, we give a generalized routing …