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Navigation on temporal networks
Omar F Robledo1, Petter Holme2,3, Huijuan Wang1
1Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, Delft, The Netherlands.
Applied Network Science
|March 24, 2025
Summary
This study introduces a new framework for routing information on temporal networks by defining distance metrics. These metrics help decide when to forward information, improving navigation efficiency in dynamic networks.
Area of Science:
- Network Science
- Computer Science
- Information Theory
Background:
- Temporal networks model dynamic interactions, crucial for mobile and social systems.
- Information transfer in these networks depends on changing connectivity over time.
- Routing in temporal networks requires strategies that account for time-varying topology.
Purpose of the Study:
- To develop a framework for designing navigation algorithms on temporal networks.
- To define and compute distance metrics for routing decisions.
- To evaluate the effectiveness of these metrics in empirical temporal networks.
Main Methods:
- Introduced a navigation algorithm framework based on a defined distance metric.
- Proposed systematic distance metrics capturing temporal network properties.
- Evaluated routing strategies using empirical contact network data.
Main Results:
- Developed a distance metric-based framework for temporal network navigation.
- Empirical evaluations showed performance variations based on metric choice.
- Metric stability in ranking node distances correlated with routing success.
Conclusions:
- The proposed framework offers a systematic approach to temporal network navigation.
- Distance metric selection significantly impacts routing efficiency and reachability.
- Findings provide insights for designing and optimizing routing strategies in dynamic networks.
