Levelwise Search and Borders of Theories in KnowledgeDiscovery
Data Mining and Knowledge Discovery
Handbook of Graphs and Networks: From the Genome to the Internet
Handbook of Graphs and Networks: From the Genome to the Internet
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Information diffusion through blogspace
Proceedings of the 13th international conference on World Wide Web
Monte Carlo Statistical Methods (Springer Texts in Statistics)
Monte Carlo Statistical Methods (Springer Texts in Statistics)
Pocket switched networks and human mobility in conference environments
Proceedings of the 2005 ACM SIGCOMM workshop on Delay-tolerant networking
CRAWDAD: A Community Resource for Archiving Wireless Data at Dartmouth
IEEE Pervasive Computing
Reality mining: sensing complex social systems
Personal and Ubiquitous Computing
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Constraint-based concept mining and its application to microarray data analysis
Intelligent Data Analysis
Impact of Human Mobility on Opportunistic Forwarding Algorithms
IEEE Transactions on Mobile Computing
Structural and temporal analysis of the blogosphere through community factorization
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
A framework for community identification in dynamic social networks
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
CTG: a connectivity trace generator for testing the performance of opportunistic mobile systems
Proceedings of the the 6th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
Realistic, mathematically tractable graph generation and evolution, using kronecker multiplication
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
A methodology to identify characteristics of the dynamic of mobile networks
Proceedings of the 4th Asian Conference on Internet Engineering
Detecting dynamic communities in opportunistic networks
ICUFN'09 Proceedings of the first international conference on Ubiquitous and future networks
ISWC '09 Proceedings of the 8th International Semantic Web Conference
MobiOpp '10 Proceedings of the Second International Workshop on Mobile Opportunistic Networking
Know thy neighbor: towards optimal mapping of contacts to social graphs for DTN routing
INFOCOM'10 Proceedings of the 29th conference on Information communications
Social dynamics in conferences: analyses of data from the live social semantics application
ISWC'10 Proceedings of the 9th international semantic web conference on The semantic web - Volume Part II
Fast track article: Connectivity in time-graphs
Pervasive and Mobile Computing
Putting contacts into context: mobility modeling beyond inter-contact times
MobiHoc '11 Proceedings of the Twelfth ACM International Symposium on Mobile Ad Hoc Networking and Computing
Semantics, sensors, and the social web: the live social semantics experiments
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part II
Centrality prediction in dynamic human contact networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
ICALP'12 Proceedings of the 39th international colloquium conference on Automata, Languages, and Programming - Volume Part II
Information and Computation
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During the last decade, the study of large scale complex networks has attracted a substantial amount of attention and works from several domains: sociology, biology, computer science, epidemiology. Most of such complex networks are inherently dynamic, with new vertices and links appearing while some old ones disappear. Until recently, the dynamics of these networks was less studied and there is a strong need for dynamic network models in order to sustain protocol performance evaluations and fundamental analyzes in all the research domains listed above. We propose in this paper a novel framework for the study of dynamic mobility networks. We address the characterization of dynamics by proposing an in-depth description and analysis of two real-world data sets. We show in particular that links creation and deletion processes are independent of other graph properties and that such networks exhibit a large number of possible configurations, from sparse to dense. From those observations, we propose simple yet very accurate models that allow generate random mobility graphs with similar temporal behavior as the one observed in experimental data.