Abstract
This work bridges the gap between distributed and centralised models of computing in the context of sublinear-time graph algorithms. A priori, typical centralised models of computing (e.g., parallel decision trees or centralised local algorithms) seem to be much more powerful than distributed message-passing algorithms: centralised algorithms can directly probe any part of the input, while in distributed algorithms nodes can only communicate with their immediate neighbours. We show that for a large class of graph problems, this extra freedom does not help centralised algorithms at all: efficient stateless deterministic centralised local algorithms can be simulated with efficient distributed message-passing algorithms. In particular, this enables us to transfer existing lower bound results from distributed algorithms to centralised local algorithms.
Original language | English |
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Title of host publication | Distributed Computing - 30th International Symposium, DISC 2016, Proceedings |
Editors | Cyril Gavoille, David Ilcinkas |
Publisher | Springer Verlag |
Pages | 201-214 |
Number of pages | 14 |
ISBN (Print) | 9783662534250 |
DOIs | |
State | Published - 2016 |
Externally published | Yes |
Event | 30th International Symposium on Distributed Computing, DISC 2016 - Paris, France Duration: 27 Sep 2016 → 29 Sep 2016 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 9888 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 30th International Symposium on Distributed Computing, DISC 2016 |
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Country/Territory | France |
City | Paris |
Period | 27/09/16 → 29/09/16 |
Bibliographical note
Publisher Copyright:© Springer-Verlag Berlin Heidelberg 2016.