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Balanced Allocations: The Heavily Loaded Case

Content Provider	Society for Industrial and Applied Mathematics (SIAM)
Author	Berenbrink, Petra Czumaj, Artur Steger, Angelika Vcking, Berthold
Copyright Year	2006
Abstract	We investigate balls-into-bins processes allocating m balls into n bins based on the multiple-choice paradigm. In the classical single-choice variant each ball is placed into a bin selected uniformly at random. In a multiple-choice process each ball can be placed into one out of $d \ge 2$ randomly selected bins. It is known that in many scenarios having more than one choice for each ball can improve the load balance significantly. Formal analyses of this phenomenon prior to this work considered mostly the lightly loaded case, that is, when $m \approx n$. In this paper we present the first tight analysis in the heavily loaded case, that is, when $m \gg n$ rather than $m \approx n$.The best previously known results for the multiple-choice processes in the heavily loaded case were obtained using majorization by the single-choice process. This yields an upper bound of the maximum load of bins of $m/n + {\mbox{$\cal O$}}(\sqrt{m \ln n \,/\, n})$ with high probability. We show, however, that the multiple-choice processes are fundamentally different from the single-choice variant in that they have "short memory." The great consequence of this property is that the deviation of the multiple-choice processes from the optimal allocation (that is, the allocation in which each bin has either $\lfloor m/n \rfloor$ or $\lceil m/n \rceil$ balls) does not increase with the number of balls as in the case of the single-choice process. In particular, we investigate the allocation obtained by two different multiple-choice allocation schemes, the greedy scheme due to Azar et al. and the always-go-left scheme due to Vcking. We show that these schemes result in a maximum load of only $m/n + {\mbox{$\cal O$}}(\ln \ln n)$ with high probability. All our detailed bounds on the maximum load are tight up to an additive constant.Furthermore, we investigate the two multiple-choice algorithms in a comparative study. We present a majorization result showing that the always-go-left scheme obtains a better load balancing than the greedy scheme for any choice of n, m, and d.
Starting Page	1350
Ending Page	1385
Page Count	36
File Format	PDF
ISSN	00975397
DOI	10.1137/S009753970444435X
e-ISSN	10957111
Journal	SIAM Journal on Computing (SMJCAT)
Issue Number	6
Volume Number	35
Language	English
Publisher	Society for Industrial and Applied Mathematics
Publisher Date	2006-07-27
Access Restriction	Subscribed
Subject Keyword	occupancy problems randomized resource allocation Applications Randomized algorithms Distributed algorithms balls-into-bins processes
Content Type	Text
Resource Type	Article
Subject	Mathematics Computer Science

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