Parallel randomized load balancing

@inproceedings{Adler1998ParallelRL,
  title={Parallel randomized load balancing},
  author={Micah Adler and Soumen Chakrabarti and Michael Mitzenmacher and Lars K. Rasmussen},
  year={1998}
}
It is well known that after placing n balls independently and uniformly at random into n bins, the fullest bin holds Θ(log n/log log n) balls with high probability. More recently, Azar et al. analyzed the following process: randomly choose d bins for each ball, and then place the balls, one by one, into the least full bin from its d choices. Azar et al. They show that after all n balls have been placed, the fullest bin contains only log log n/log d+Θ(1) balls with high probability. We explore… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 115 CITATIONS

The power of $d$-thinning in load balancing

VIEW 9 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

Self-Stabilizing Balls and Bins in Batches

VIEW 10 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

Self-stabilizing Balls & Bins in Batches: The Power of Leaky Bins [Extended Abstract]

VIEW 10 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

The 1-2-3-Toolkit for Building Your Own Balls-into-Bins Algorithm

VIEW 9 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Multiple-Choice Balanced Allocation in (Almost) Parallel

VIEW 10 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Revisiting randomized parallel load balancing algorithms

VIEW 10 EXCERPTS
CITES BACKGROUND
HIGHLY INFLUENCED

Parallel randomized load balancing: A lower bound for a more general model

VIEW 10 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

Randomised load balancing

VIEW 11 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

FILTER CITATIONS BY YEAR

1996
2019

CITATION STATISTICS

  • 15 Highly Influenced Citations

  • Averaged 8 Citations per year from 2017 through 2019