News/blog Contact

Randomized Distributed Online Algorithms Against Adaptive Offline Adversaries.
Joan Boyar, Faith Ellen, and Kim S. Larsen.
Information Processing Letters, 161: Article No. 105973, 2020.
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.


publication
Link to the publication at the publisher's site - subscription may be required.
Text required by the publisher (if any): The publication is available from ScienceDirect.

open access (204 KB)
The same as the publisher's version, when the publisher permits. Otherwise, the author's last version before the publisher's copyright; this is often exactly the same, but sometimes fonts, page numbers, figure numbers, etc. are different. It may also be a full version. However, it is safe to read this version, and at the same time cite the official version, as long as references to concrete locations, numbered theorems, etc. inside the article are avoided.

other publications
Other publications by the author.