TY - GEN
T1 - Non-local probes do not help with many graph problems
AU - Göös, Mika
AU - Hirvonen, Juho
AU - Levi, Reut
AU - Medina, Moti
AU - Suomela, Jukka
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2016.
PY - 2016/1/1
Y1 - 2016/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84988569110&partnerID=8YFLogxK
U2 - 10.1007/978-3-662-53426-7_15
DO - 10.1007/978-3-662-53426-7_15
M3 - Conference contribution
AN - SCOPUS:84988569110
SN - 9783662534250
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 201
EP - 214
BT - Distributed Computing - 30th International Symposium, DISC 2016, Proceedings
A2 - Gavoille, Cyril
A2 - Ilcinkas, David
PB - Springer Verlag
T2 - 30th International Symposium on Distributed Computing, DISC 2016
Y2 - 27 September 2016 through 29 September 2016
ER -