Resource type
Thesis type
(Thesis) Ph.D.
Date created
2017-09-22
Authors/Contributors
Author: Mallmann-Trenn, Frederik
Abstract
This thesis is devoted to the study of stochastic decentralized processes. Typical examples in the real world include the dynamics of weather and temperature, of traffic, the way we meet our friends, etc. We take the rich tool set from probability theory for the analysis of Markov Chains and employ it to study a wide range of such distributed processes: Forest Fire Model (social networks), Balls-into-Bins with Deleting Bins, and fundamental consensus dynamics and protocols such as the Voter Model, 2-Choices, and 3-Majority.
Document
Identifier
etd10387
Copyright statement
Copyright is held by the author.
Scholarly level
Supervisor or Senior Supervisor
Thesis advisor: Berenbrink, Petra
Thesis advisor: Mathieu, Claire
Member of collection
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etd10387_FMallmann-Trenn.pdf | 2.23 MB |