Tight bounds for fractional and randomized truthful scheduling
Georgios Anastasiadis, George Christodoulou, Elias Koutsoupias, Annamaria Kovacs, Conrad Schecker
Abstract
We resolve one of the longest-standing open problems in algorithmic mechanism design by showing that randomization cannot yield a sublinear approximation for truthful scheduling on unrelated machines, even when truthfulness is required only in expectation. Our main technical result concerns fractional scheduling, where tasks may be split among machines. We prove that every deterministic truthful fractional mechanism on n unrelated machines has worst-case approximation ratio at least (n+1)/2, even against the optimal integral makespan. This matches the known upper bound exactly and settles the optimal approximation ratio of truthful fractional scheduling. Since the expected allocations and payments of a truthful-in-expectation mechanism define a truthful fractional mechanism, the same lower bound applies to all truthful-in-expectation mechanisms and, in particular, to all universally truthful mechanisms. On the positive side, we give a universally truthful mechanism with approximation ratio n/2+o(n). Together, these results establish the optimal leading constant 1/2 for randomized truthful scheduling. Thus, randomization improves on the optimal deterministic approximation ratio by an asymptotic factor of two, and no more.
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