Title
Self-Stabilizing Repeated Balls-into-Bins.
Abstract
We study the following synchronous process that we call repeated balls-into-bins. The process is started by assigning n balls to n bins in an arbitrary way. Then, in every subsequent round, one ball is chosen according to some fixed strategy (random, FIFO, etc) from each non-empty bin, and re-assigned to one of the n bins uniformly at random. This process corresponds to a non-reversible Markov chain and our aim is to study its self-stabilization properties with respect to the maximum(bin) load and some related performance measures. We define a configuration (i.e., a state) legitimate if its maximum load is O(log n). We first prove that, starting from any legitimate configuration, the process will only take on legitimate configurations over a period of length bounded by any polynomial in n, with high probability (w.h.p.). Further we prove that, starting from any configuration, the process converges to a legitimate configuration in linear time, w.h.p. This implies that the process is self-stabilizing w.h.p. and, moreover, that every ball traverses all bins in O(n log2 n) rounds, w.h.p. The latter result can also be interpreted as an almost tight bound on the cover time for the problem of parallel resource assignment in the complete graph.
Year
DOI
Venue
2015
10.1145/2755573.2755584
ACM Symposium on Parallelism in Algorithms and Architectures
Keywords
Field
DocType
Balls into Bins,Self-Stabilizing Systems,Markov Chains,Parallel Resource Assignment
Complete graph,Polynomial,Bin,Computer science,Ball (bearing),Markov chain,Self-stabilization,Time complexity,Distributed computing,Bounded function
Journal
Volume
Citations 
PageRank 
abs/1501.04822
4
0.42
References 
Authors
19
5
Name
Order
Citations
PageRank
Luca Becchetti194555.75
Andrea E. F. Clementi2116885.30
Emanuele Natale37414.52
Francesco Pasquale442128.22
Gustavo Posta540.42