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Contention Resolution with Heterogeneous Job Sizes

机译:具有不同工作规模的竞争解决

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We study the problem of contention resolution for different-sized jobs on a simple channel. When a job makes a run attempt, it learns only whether the attempt succeeded or failed. We first analyze binary exponential backoff, and show that it achieves a makespan of V2~(Θ((log n)~(1/2))) with high probability, where V is the total work of all n contending jobs. This bound is significantly larger than when jobs are constant sized. A variant of exponential backoff, however, achieves makespan O(V log V) with high probability. Finally, we introduce a new protocol, size-hashed backoff, specifically designed for jobs of multiple sizes that achieves makespan O(V log~3 log V). The error probability of the first two bounds is polynomially small in n and the latter is polynomially small in log V.
机译:我们在一个简单的渠道上研究了不同规模作业的争用解决问题。当作业尝试运行时,它仅了解尝试是成功还是失败。我们首先分析二进制指数退避,并证明它具有很高的概率达到V2〜(Θ((log n)〜(1/2))),其中V是所有n个竞争工作的总功。此界限比固定大小的作业大得多。但是,指数补偿的一种变体可以极高地实现制造跨度O(V log V)。最后,我们引入了一种新的协议,即大小哈希退避,该协议专为多种大小的作业而设计,可实现makepan O(V log〜3 log V)。前两个边界的错误概率在n处为多项式较小,而在log V中后者的多项式为较小。

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