Randomized distributed online algorithms against adaptive offline adversaries

In the sequential setting, a decades-old fundamental result in online algorithms states that if there is a c-competitive randomized online algorithm against an adaptive, offline adversary, then there is a c-competitive deterministic algorithm. The adaptive, offline adversary is the strongest adversa...

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Bibliographic Details
Published in:Information processing letters Vol. 161; p. 105973
Main Authors: Boyar, Joan, Ellen, Faith, Larsen, Kim S.
Format: Journal Article
Language:English
Published: Elsevier B.V 01.09.2020
Subjects:
Adaptive offline adversary
Distributed systems
Online algorithms
Randomized algorithms
Online algorithms
Randomized algorithms
Distributed systems
Adaptive offline adversary
ISSN:0020-0190, 1872-6119
Online Access:Get full text
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Summary:In the sequential setting, a decades-old fundamental result in online algorithms states that if there is a c-competitive randomized online algorithm against an adaptive, offline adversary, then there is a c-competitive deterministic algorithm. The adaptive, offline adversary is the strongest adversary among the ones usually considered, so the result states that if one has to be competitive against such a strong adversary, then randomization does not help. This implies that researchers do not consider randomization against an adaptive, offline adversary. We prove that in a distributed setting, this result does not necessarily hold, so randomization against an adaptive, offline adversary becomes interesting again. •A fundamental online algorithms result does not hold in a distributed setting.•Randomized distributed online against adaptive offline can beat deterministic.•Reviving randomized online against adaptive offline in distributed settings.
ISSN:0020-0190
1872-6119
DOI:10.1016/j.ipl.2020.105973