Almost random graphs with simple hash functions

Almost random graphs with simple hash functions
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具有简单哈希函数的几乎随机图

DOI:
10.1145/780542.780634
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发表时间:
2003
期刊:
ACM Trans. Algorithms
影响因子:
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通讯作者:
Philipp Woelfel
Philipp Woelfel
中科院分区:
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文献类型:
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作者:
Martin Dietzfelbinger;Philipp Woelfel

文献摘要

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我们描述一种简单的随机构造方法,用于从全集\(U\)生成哈希函数对\(h_1\),\(h_2\),其值域\(V = [m] = \{0, 1, \ldots, m - 1\}\)且\(W = [m]\),使得对于每个键集\(S \subseteq U\),其中\(n = |S| \leq m / (1 + \varepsilon)\),具有节点集\(V \cup W\)和边集\(\{(h_1(x), h_2(x)) | x \in S\}\)的(随机)二分(多重)图呈现出一种本质上随机的结构。该构造将\(d\)元独立类(\(d\)为相对较小的常数)与著名的随机偏移技术相结合。在将存储\(h_1\)和\(h_2\)的描述所需空间保持在\(O(n^{\zeta})\)(对于任意固定的\(\zeta < 1\))的同时,我们获得了比此前此类构造(涉及西格尔的高性能哈希类)小得多的(常数)求值时间。主要的新技术是对图结构和哈希函数内部结构的联合分析,以及一种观察随机(多重)图的圈结构的新方法。这种构造可用于改进帕格和罗德勒的“布谷鸟哈希”(2001年),为模拟键集\(S\)上的均匀哈希获得一种比奥斯特林和帕格(2002/2003年)近期构造更简单且更快的替代方法,并用于在分布式内存机器上模拟共享内存。我们还描述了一种不使用多项式实现(近似)\(d\)元独立哈希的新方法。
We describe a simple randomized construction for generating pairs of hash functions h1,h2 from a universe U to ranges V = [m] = (0,1,...,m-1) and W = [m] so that for every key set S ⊆ U with n = |S| ≤ m/(1 + ε) the (random) bipartite (multi)graph with node set V ∪ W and edge set (h1(x),h2(x))| x ∈ S exhibits a structure that is essentially random. The construction combines d-wise independent classes for d a relatively small constant with the well-known technique of random offsets. While keeping the space needed to store the description of h1 and h2 at O(nζ), for ζ < 1 fixed arbitrarily, we obtain a much smaller (constant) evaluation time than previous constructions of this kind, which involved Siegel's high-performance hash classes. The main new technique is the combined analysis of the graph structure and the inner structure of the hash functions, as well as a new way of looking at the cycle structure of random (multi)graphs. The construction may be applied to improve on Pagh and Rodler's "cuckoo hashing" (2001), to obtain a simpler and faster alternative to a recent construction of Ostlin and Pagh (2002/03) for simulating uniform hashing on a key set S, and to the simulation of shared memory on distributed memory machines. We also describe a novel way of implementing (approximate) d-wise independent hashing without using polynomials.