The power of two choices in graphical allocation

Nikhil Bansal, Ohad N. Feldheim

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

4 Scopus citations


The graphical balls-into-bins process is a generalization of the classical 2-choice balls-into-bins process, where the bins correspond to vertices of an arbitrary underlying graph G. At each time step an edge of G is chosen uniformly at random, and a ball must be assigned to either of the two endpoints of this edge. The standard 2-choice process corresponds to the case of G=Kn. For any k(n)-edge-connected, d(n)-regular graph on n vertices, and any number of balls, we give an allocation strategy that, with high probability, ensures a gap of O((d/k) log4n loglogn), between the load of any two bins. In particular, this implies polylogarithmic bounds for natural graphs such as cycles and tori, for which the classical greedy allocation strategy is conjectured to have a polynomial gap between the bin loads. For every graph G, we also show an ω((d/k) + logn) lower bound on the gap achievable by any allocation strategy. This implies that our strategy achieves the optimal gap, up to polylogarithmic factors, for every graph G. Our allocation algorithm is simple to implement and requires only O(log(n)) time per allocation. It can be viewed as a more global version of the greedy strategy that compares average load on certain fixed sets of vertices, rather than on individual vertices. A key idea is to relate the problem of designing a good allocation strategy to that of finding suitable multi-commodity flows. To this end, we consider Räcke's cut-based decomposition tree and define certain orthogonal flows on it.

Original languageAmerican English
Title of host publicationSTOC 2022 - Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing
EditorsStefano Leonardi, Anupam Gupta
PublisherAssociation for Computing Machinery
Number of pages12
ISBN (Electronic)9781450392648
StatePublished - 6 Sep 2022
Event54th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2022 - Rome, Italy
Duration: 20 Jun 202224 Jun 2022

Publication series

NameProceedings of the Annual ACM Symposium on Theory of Computing
ISSN (Print)0737-8017


Conference54th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2022

Bibliographical note

Publisher Copyright:
© 2022 ACM.


  • Balls-into-bins processes
  • Load-balancing
  • Racke decomposition
  • graphical two-choice


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