Succinct representations of arbitrary graphs

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Abstract

We consider the problem of encoding a graph with n vertices and m edges compactly supporting adjacency, neighborhood and degree queries in constant time in the logn-bit word RAM model. The adjacency query asks whether there is an edge between two vertices, the neighborhood query reports the neighbors of a given vertex in constant time per neighbor, and the degree query reports the number of incident edges to a given vertex. We study the problem in the context of succinctness, where the goal is to achieve the optimal space requirement as a function of n and m, to within lower order terms. We prove a lower bound in the cell probe model that it is impossible to achieve the information-theory lower bound within lower order terms unless the graph is too sparse (namely m = o(n δ ) for any constant δ > 0) or too dense (namely m = ω(n 2 - δ ) for any constant δ > 0). Furthermore, we present a succinct encoding for graphs for all values of n,m supporting queries in constant time. The space requirement of the representation is always within a multiplicative 1 + ε factor of the information-theory lower bound for any arbitrarily small constant ε > 0. This is the best achievable space bound according to our lower bound where it applies. The space requirement of the representation achieves the information-theory lower bound tightly within lower order terms when the graph is sparse (m = o(n δ ) for any constant δ > 0). © 2008 Springer-Verlag Berlin Heidelberg.

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Farzan, A., & Munro, J. I. (2008). Succinct representations of arbitrary graphs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5193 LNCS, pp. 393–404). Springer Verlag. https://doi.org/10.1007/978-3-540-87744-8_33

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