Competition-driven modeling of temporal networks
| Autor: | Nikolay Yakovets, George H. L. Fletcher, Kaijie Zhu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Scale (ratio)
Degree (graph theory) Computer science Distributed computing Node (networking) Concurrent set size Computer applications to medicine. Medical informatics Process (computing) Modeling R858-859.7 Timeline Temporal networks 01 natural sciences 010305 fluids & plasmas Computer Science Applications Competition (economics) Set (abstract data type) Computational Mathematics Cardinality Modeling and Simulation 0103 physical sciences 010306 general physics |
| Zdroj: | EPJ Data Science, Vol 10, Iss 1, Pp 1-24 (2021) |
| ISSN: | 2193-1127 |
| Popis: | We study the problem of modeling temporal networks constrained by the size of a concurrent set, a characteristic of temporal networks shown to be important in many application areas, e.g., in transportation, social, process, and other networks. We propose a competition-driven model for the generation of such constrained networks. Our method carries out turns of competitions along the timeline where each node in a network is labeled with a probability to gain outgoing edges in competitions. We present a thorough theoretical analysis to investigate the cardinality and degree distributions of the generated networks. Our experimental results demonstrate that our model simulates real-world networks well and generates networks efficiently and at scale. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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