Randomized algorithms for online vector load balancing

Yossi Azar, Ilan Reuven Cohen, Debmalya Panigrahi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

We study randomized algorithms for the online vector bin packing and vector scheduling problems. For vector bin packing, we achieve a competitive ratio of ~O(d1=B), where d is the number of dimensions and B the size of a bin. This improves the previous bound of Õ(d1B)) by a polynomial factor, and is tight up to logarithmic factors. For vector scheduling, we show a lower bound of ( log d log log d ) on the competitive ratio of randomized algorithms, which is the first result for randomized algorithms and is asymptotically tight. Finally, we analyze the widely used "power of two choices' algorithm for vector scheduling, and show that its competitive ratio is O(log log n+ log d log log d ), which is optimal up to the additive O(log log n) term that also appears in the scalar version of this algorithm.

Original languageEnglish
Title of host publication29th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2018
EditorsArtur Czumaj
PublisherAssociation for Computing Machinery
Pages990-991
Number of pages2
ISBN (Electronic)9781611975031
DOIs
StatePublished - 2018
Event29th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2018 - New Orleans, United States
Duration: 7 Jan 201810 Jan 2018

Publication series

NameProceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms

Conference

Conference29th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2018
Country/TerritoryUnited States
CityNew Orleans
Period7/01/1810/01/18

Funding

FundersFunder number
National Science FoundationCCF-1527084andCCF-1535972

    Fingerprint

    Dive into the research topics of 'Randomized algorithms for online vector load balancing'. Together they form a unique fingerprint.

    Cite this