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DYNAMICMARCH SIGNED

Dynamics of Multiple, Interacting and Concurrent Markov Chains

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Project "DYNAMICMARCH" data sheet

The following table provides information about the project.

Coordinator
THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE 

Organization address
address: TRINITY LANE THE OLD SCHOOLS
city: CAMBRIDGE
postcode: CB2 1TN
website: www.cam.ac.uk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Total cost 1˙400˙789 €
 EC max contribution 1˙400˙789 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2015-STG
 Funding Scheme ERC-STG
 Starting year 2016
 Duration (year-month-day) from 2016-05-01   to  2021-04-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE UK (CAMBRIDGE) coordinator 1˙400˙789.00

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 Project objective

Markov chains are fundamental processes and have been studied in nearly every scientific discipline in the past 100 years. In computer science, reversible Markov chains, also known as random walks, form the basis of many efficient randomised algorithms which have been successfully applied to a variety of complex sampling, learning and optimisation problems.

Nowadays an increasing number of algorithms and processes on networks are based on multiple (concurrent and possibly dependent) random walks, including algorithms for packet routing, content search, graph clustering, link prediction and website ranking. This trend will be reinforced by the steady growth of large-scale networks and massive data sets. However, the existing theory of single random walks is not well-suited to cope with the complexity inherent to multiple random walks, and even for independent walks many fundamental questions remain open.

The goal of this proposal is to develop a systematic and rigorous study of multiple random walks. First, we will analyse this random process via commonly used metrics such as hitting times, cover times, mixing times as well as new quantities which are unique to multiple random walks. Then we will connect these quantities to structural properties of the underlying graph. Finally, these insights will be applied to the design of new efficient randomised algorithms for large graphs and distributed networks.

 Publications

year authors and title journal last update
List of publications.
2019 Varun Kanade, Frederik-Mallmann-Trenn, Thomas Sauerwald
On coalescence time in graphs: When is coalescing as fast as meeting?: Extended Abstract
published pages: , ISSN: , DOI:
Proceedings of the 30th Annual ACM-SIAM Symposium on Discrete Algorithms 2020-01-20
2019 Nicolas Rivera, Thomas Sauerwald, Alexandre Stauffer, John Sylvester
The dispersion time of random walks on finite graphs
published pages: , ISSN: , DOI:
Proceedings of the 31st ACM Symposium on Parallelism in Algorithms and Architectures 2020-01-20
2017 Leran Cai, Thomas Sauerwald
Randomized Load Balancing on Networks with Stochastic Inputs
published pages: 139:1--139:14, ISSN: , DOI:
Proceedings of the 44th International Colloquium on Automata, Languages, and Programming (ICALP) 2020-01-20
2017 Thomas Sauerwald
Multiple Random Walks
published pages: 60-61, ISSN: 1868-8969, DOI:
Science & Technology 24 2020-01-20
2017 Andrej Ivaskovic, Adrian Kosowski, Dominik Pajak, Thomas Sauerwald
Multiple Random Walks on Paths and Grids
published pages: 44:1--44:14, ISSN: 1868-8969, DOI: 10.4230/LIPIcs.STACS.2017.44
34th Symposium on Theoretical Aspects of Computer Science (STACS 2017) 66 2020-01-20

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