Coloring temporal graphs

2022 ◽  
Vol 123 ◽  
pp. 171-185
Author(s):  
Andrea Marino ◽  
Ana Silva
Keyword(s):  
Temporal Graphs

scholarly journals Efficient distributed reachability querying of massive temporal graphs

2019 ◽  
Vol 28 (6) ◽  
pp. 871-896 ◽  
Author(s):  
Tianming Zhang ◽  
Yunjun Gao ◽  
Lu Chen ◽  
Wei Guo ◽  
Shiliang Pu ◽  
...  
Keyword(s):  
Temporal Graphs

Modeling consistency of spatio-temporal graphs

2013 ◽  
Vol 84 ◽  
pp. 59-80 ◽  
Author(s):  
G. Del Mondo ◽  
M.A. Rodríguez ◽  
C. Claramunt ◽  
L. Bravo ◽  
R. Thibaud
Keyword(s):  
Spatio Temporal ◽  
Temporal Graphs

Span-reachability querying in large temporal graphs

2021 ◽  
Author(s):  
Dong Wen ◽  
Bohua Yang ◽  
Ying Zhang ◽  
Lu Qin ◽  
Dawei Cheng ◽  
...  
Keyword(s):  
Temporal Graphs

scholarly journals Optimizing Reachability Sets in Temporal Graphs by Delaying

2020 ◽  
Vol 34 (06) ◽  
pp. 9810-9817
Author(s):  
Argyrios Deligkas ◽  
Igor Potapov
Keyword(s):  
Polynomial Time Algorithm ◽  
Time Algorithm ◽  
Control Mechanisms ◽  
Scheduling Problems ◽  
Dynamic Graph ◽  
Time Step ◽  
Supply Networks ◽  
Reachability Sets ◽  
Network Epidemiology ◽  
Temporal Graphs

A temporal graph is a dynamic graph where every edge is assigned a set of integer time labels that indicate at which discrete time step the edge is available. In this paper, we study how changes of the time labels, corresponding to delays on the availability of the edges, affect the reachability sets from given sources. The questions about reachability sets are motivated by numerous applications of temporal graphs in network epidemiology and scheduling problems in supply networks in manufacturing. We introduce control mechanisms for reachability sets that are based on two natural operations of delaying time events. The first operation, termed merging, is global and batches together consecutive time labels in the whole network simultaneously. This corresponds to postponing all events until a particular time. The second, imposes independent delays on the time labels of every edge of the graph. We provide a thorough investigation of the computational complexity of different objectives related to reachability sets when these operations are used. For the merging operation, we prove NP-hardness results for several minimization and maximization reachability objectives, even for very simple graph structures. For the second operation, we prove that the minimization problems are NP-hard when the number of allowed delays is bounded. We complement this with a polynomial-time algorithm for the case of unbounded delays.

scholarly journals Edge-Disjoint Branchings in Temporal Graphs

2020 ◽  
pp. 112-125 ◽  
Author(s):  
Victor Campos ◽  
Raul Lopes ◽  
Andrea Marino ◽  
Ana Silva
Keyword(s):  
Edge Disjoint ◽  
Temporal Graphs

Time-topology analysis

2021 ◽  
Vol 14 (13) ◽  
pp. 3322-3334
Author(s):  
Yunkai Lou ◽  
Chaokun Wang ◽  
Tiankai Gu ◽  
Hao Feng ◽  
Jun Chen ◽  
...  
Keyword(s):  
Temporal Information ◽  
Time Dimension ◽  
Topology Analysis ◽  
Topological Information ◽  
Analysis Methods ◽  
Short Period ◽  
Pruning Strategy ◽  
Temporal Graph ◽  
Types Of Information ◽  
Temporal Graphs

Many real-world networks have been evolving, and are finely modeled as temporal graphs from the viewpoint of the graph theory. A temporal graph is informative, and always contains two types of information, i.e., the temporal information and topological information, where the temporal information reflects the time when the relationships are established, and the topological information focuses on the structure of the graph. In this paper, we perform time-topology analysis on temporal graphs to extract useful information. Firstly, a new metric named T-cohesiveness is proposed to evaluate the cohesiveness of a temporal subgraph. It defines the cohesiveness of a temporal subgraph from the time and topology dimensions jointly. Specifically, given a temporal graph G s = ( Vs , ε Es ), cohesiveness in the time dimension reflects whether the connections in G s happen in a short period of time, while cohesiveness in the topology dimension indicates whether the vertices in V s are densely connected and have few connections with vertices out of G s . Then, T-cohesiveness is utilized to perform time-topology analysis on temporal graphs, and two time-topology analysis methods are proposed. In detail, T-cohesiveness evolution tracking traces the evolution of the T-cohesiveness of a subgraph, and combo searching finds out all the subgraphs that contain the query vertex and have T-cohesiveness larger than a given threshold. Moreover, a pruning strategy is proposed to improve the efficiency of combo searching. Experimental results confirm the efficiency of the proposed time-topology analysis methods and the pruning strategy.

On Short Fastest Paths in Temporal Graphs

2021 ◽  
pp. 40-51
Author(s):  
Umesh Sandeep Danda ◽  
G. Ramakrishna ◽  
Jens M. Schmidt ◽  
M. Srikanth
Keyword(s):  
Temporal Graphs

Efficiently Answering Span-Reachability Queries in Large Temporal Graphs

2020 ◽  
Author(s):  
Dong Wen ◽  
Yilun Huang ◽  
Ying Zhang ◽  
Lu Qin ◽  
Wenjie Zhang ◽  
...  
Keyword(s):  
Reachability Queries ◽  
Temporal Graphs
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