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Memoryless Algorithms for the Generalized k-server Problem on Uniform Metrics

机译:统一度量下广义k-server问题的无记忆算法

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We consider the generalized k-server problem on uniform metrics. We study the power of memoryless algorithms and show tight bounds of Θ(k!) on their competitive ratio. In particular we show that the Harmonic Algorithm achieves this competitive ratio and provide matching lower bounds. Combined with the ≈2~(2~k) doubly-exponential bound of Chiplunkar and Vishwanathan for the more general setting of memoryless algorithms on uniform metrics with different weights, this shows that the problem becomes exponentially easier when all weights are equal.
机译:我们考虑了统一度量上的广义K-Server问题。我们研究了无记忆算法的能力,并给出了Θ(k!)的紧界他们的竞争比例。特别地,我们证明了调和算法达到了这个竞争比,并提供了匹配下界。再加上≈2~(2~k)Chiplunkar和Vishwanathan的双指数界对于具有不同权重的一致度量上更一般的无记忆算法设置,这表明当所有权重相等时,问题变得指数容易。

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