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Lower bounds for distributed coin-flipping and randomized consensusby: James Aspnes
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AbstractWe examine a class of collective coin-flipping games that arises from randomized distributed algorithms with halting failures. In these games, a sequence of local coin flips is generated, which must be combined to form a single global coin flip. An adversary monitors the game and may attempt to bias its outcome by hiding the result of up to t local coin flips. We show that to guarantee at most constant bias,ΩΓ t 2 ) local coins are needed, even if (a) the local coins can have...
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