Rejection-Based Simulation of Stochastic Spreading Processes on Complex Networks
Stochastic processes can model many emerging phenomena on networks, like the spread of computer viruses, rumors, or infectious diseases. Understanding the dynamics of such stochastic spreading processes is therefore of fundamental interest. In this work we consider the wide-spread compartment model where each node is in one of several states (or compartments). Nodes change their state randomly after an exponentially distributed waiting time and according to a given set of rules. For networks of realistic size, even the generation of only a single stochastic trajectory of a spreading process is computationally very expensive.
Here, we propose a novel simulation approach, which combines the advantages of event-based simulation and rejection sampling. Our method outperforms state-of-the-art methods in terms of absolute runtime and scales significantly better while being statistically equivalent.
Sun 7 AprDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
11:00 - 12:30 | |||
11:00 30mTalk | Fixed-point Computation of Equilibria in Biochemical Regulatory Networks HSB Isabel Cristina Perez-Verona IMT Institute for Advanced Studies Lucca, Italy, Mirco Tribastone IMT Institute for Advanced Studies Lucca, Italy, Max Tschaikowski IMT Institute for Advanced Studies Lucca, Italy | ||
11:30 30mTalk | Rejection-Based Simulation of Stochastic Spreading Processes on Complex Networks HSB | ||
12:00 30mTalk | rPrism -- A software for reactive weighted state transition models HSB Daniel Figueiredo University of Aveiro, Eugénio A. M. Rocha University of Aveiro, Madalena Chaves INRIA, Manuel A. Martins University of Aveiro |