Balanced allocation on hypergraphs

IF 1.1 3区 计算机科学 Q1 BUSINESS, FINANCE Journal of Computer and System Sciences Pub Date : 2023-05-30 DOI:10.1016/j.jcss.2023.05.004
Catherine Greenhill , Bernard Mans , Ali Pourmiri
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引用次数: 1

Abstract

We consider a variation of balls-into-bins which randomly allocates m balls into n bins. Following Godfrey's model (SODA, 2008), we assume that each ball t, 1tm, comes with a hypergraph H(t)={B1,B2,,Bst}, and each edge BH(t) contains at least a logarithmic number of bins. Given d2, our d-choice algorithm chooses an edge BH(t), uniformly at random, and then chooses a set D of d random bins from the selected edge B. The ball is allocated to a least-loaded bin from D. We prove that if the hypergraphs H(1),,H(m) satisfy a balancedness condition and have low pair visibility, then after allocating m=Θ(n) balls, the maximum load of any bin is at most logdlogn+O(1), with high probability. Moreover, we establish a lower bound for the maximum load attained by the balanced allocation for a sequence of hypergraphs in terms of pair visibility.

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在超图上均衡分配
我们考虑将m个球随机分配到n个箱中的球到箱中的变化。根据Godfrey的模型(SODA,2008),我们假设每个球t,1⩽t \10877;m都有一个超图H(t)={B1,B2,…,Bst},并且每个边B∈H(t)至少包含对数数量的bin。给定d⩾2,我们的d-选择算法均匀随机地选择一条边B∈H(t),然后从所选边B中选择一组d个随机箱。球被分配到d中的一个负载最小的箱⁡日志⁡n+O(1),具有高概率。此外,我们根据对可见性,为超图序列的平衡分配所获得的最大负载建立了一个下界。
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来源期刊
Journal of Computer and System Sciences
Journal of Computer and System Sciences 工程技术-计算机:理论方法
CiteScore
3.70
自引率
0.00%
发文量
58
审稿时长
68 days
期刊介绍: The Journal of Computer and System Sciences publishes original research papers in computer science and related subjects in system science, with attention to the relevant mathematical theory. Applications-oriented papers may also be accepted and they are expected to contain deep analytic evaluation of the proposed solutions. Research areas include traditional subjects such as: • Theory of algorithms and computability • Formal languages • Automata theory Contemporary subjects such as: • Complexity theory • Algorithmic Complexity • Parallel & distributed computing • Computer networks • Neural networks • Computational learning theory • Database theory & practice • Computer modeling of complex systems • Security and Privacy.
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