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Balls into Bins via Local Search (1207.2125v1)

Published 9 Jul 2012 in math.PR, cs.DM, and math.CO

Abstract: We propose a natural process for allocating n balls into n bins that are organized as the vertices of an undirected graph G. Each ball first chooses a vertex u in G uniformly at random. Then the ball performs a local search in G starting from u until it reaches a vertex with local minimum load, where the ball is finally placed on. In our main result, we prove that this process yields a maximum load of only \Theta(\log \log n) on expander graphs. In addition, we show that for d-dimensional grids the maximum load is \Theta\Big(\big(\frac{\log n}{\log \log n}\big){\frac{1}{d+1}}\Big). Finally, for almost regular graphs with minimum degree \Omega(\log n), we prove that the maximum load is constant and also reveal a fundamental difference between random and arbitrary tie-breaking rules.

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