作者: A. Scherrer , P. Borgnat , E. Fleury , J.-L. Guillaume , C. Robardet
DOI: 10.1016/J.COMNET.2008.06.007
关键词: Theoretical computer science 、 Graph 、 Complex network 、 Network dynamics 、 Graph property 、 Network model 、 Dynamic network analysis 、 Evolving networks 、 Computer science 、 Artificial intelligence 、 Complex system 、 Random graph
摘要: During the last decade, study of large scale complex networks has attracted a substantial amount attention and works from several domains: sociology, biology, computer science, epidemiology. Most such are inherently dynamic, with new vertices links appearing while some old ones disappear. Until recently, dynamics these was less studied there is strong need for dynamic network models in order to sustain protocol performance evaluations fundamental analyzes all research domains listed above. We propose this paper novel framework mobility networks. address characterization by proposing an in-depth description analysis two real-world data sets. show particular that creation deletion processes independent other graph properties exhibit number possible configurations, sparse dense. From those observations, we simple yet very accurate allow generate random graphs similar temporal behavior as one observed experimental data.