Abstract

A time-dependent graph is, informally speaking, a graph structure dynamically changes with time. In such graphs, the weights associated with edges dynamically change over time, that is, the edges in such graphs are activated by sequences of time-dependent elements. Many real-life scenarios can be better modeled by time-dependent graphs, such as bioinformatics networks, transportation networks, and social networks. In particular, the time-dependent graph is a very broad concept, which is reflected in the related research with many names, including temporal graphs, evolving graphs, time-varying graphs, historical graphs, and so on. Though static graphs have been extensively studied, for their time-dependent generalizations, we are still far from a complete and mature theory of models and algorithms. In this paper, we discuss the definition and topological structure of time-dependent graphs, as well as models for their relationship to dynamic systems. In addition, we review some classic problems on time-dependent graphs, e.g., route planning, social analysis, and subgraph problem (including matching and mining). We also introduce existing time-dependent systems and summarize their advantages and limitations. We try to keep the descriptions consistent as much as possible and we hope the survey can help practitioners to understand existing time-dependent techniques.

Highlights

  • A graph is a data structure which is widely used in network modeling

  • Graphs are extensively applied in social networks, biological networks, transportation networks, distributed systems, and so on

  • We showed how dynamic systems benefit from the modeling of time-dependent graphs and discussed methods for discovering and analyzing dynamic network structures in the time domain

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Summary

Introduction

A graph is a data structure which is widely used in network modeling. Almost every scientific domains, including mathematics, computer science, chemistry, and biology, can be modeled and studied by graphs. Departure time of the second flight must be later than the arrival time of the first flight In such networks, the weights associated with edges dynamically change over time (time-dependency) [22]. An advantage of modeling a network as a time-dependent graph is that we can study the dynamic effect of time on the graph instead of the impact of the actual dynamics. If the dynamic system changes much faster than the speed of the dynamic connection, or if the edges in the graph are actively changing, there is no need to model the dynamic system into a time-dependent graph [33]. Though static graphs have been extensively studied, there is still far from having a concrete set of structures and algorithm frameworks for time-dependent graphs [55].

Definition
Data Modeling
Models for Discrete Time‐Dependent Graphs
Models for Continuous Time‐Dependent Graphs
Topological Structure
Time‐Respecting Paths
Connectivity, Components, and Menger’s Theorem
Spanning Tree
Time‐Dependent Route Planning
Models Based on Discrete Travel Time
Models Based on Continuous Travel Time
Multi‐criteria Route Planning
Time‐Dependent Social Analysis
Time‐Dependent Subgraph Matching
Querying Static Graph Pattern
Querying Time‐Dependent Graph Pattern
Time‐Dependent Subgraph Mining
Time‐Dependent Graph Systems
Snapshot‐Based System
Traversal‐Based System
Conclusions and Open Questions
Full Text
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