There are different motivations and applications of spreading processes on temporal graphs. They include spreading information (rumors, relevant information, ..) or infections (disease, ).

Spreading processes on temporal graphs have a variety of motivations and applications, ranging from the spreading of information (such as rumors, news, or critical updates) to the modeling of infection spreading (e.g., diseases or computer viruses). These processes serve as vital tools for understanding and predicting the behaviors in real-world networks, as well as structural properties of the theiretical concept of temporal graphs.

Research in this area typically addresses a range of computational structures and questions:

Information Dissemination (Gossip Theory)

• Broadcasting (one-to-all communication): Where one person needs to transmit information to everyone else in a network
• Gossiping (all-to-all communication): Where each person has unique information that must be shared with everyone else through phone calls or other communications

Information Dissemination

Physical Spreading

Cases where physical movement or transmission takes time, such as:

• Vehicle transportation
• Physical object movement (e.g., robots)
• Infection spreading

There are different questions to ask. These lead to different computational problems (theoretical!):

Flooding time

Multi Agent Path Finding

Firefighter

MaxSpread

We can also use the infection to find out stuff:

Network Discovery

Source Detection