Linear-Time Compression of Bounded-Genus Graphs into Information-Theoretically Optimal Number of Bits
Abstract
A compression scheme A for a class G of graphs consists of an encoding algorithm EncodeA that computes a binary string CodeA(G) for any given graph G in G and a decoding algorithm DecodeA that recovers G from CodeA(G). A compression scheme A for G is optimal if both EncodeA and DecodeA run in linear time and the number of bits of CodeA(G) for any n-node graph G in G is information-theoretically optimal to within lower-order terms. Trees and plane triangulations were the only known nontrivial graph classes that admit optimal compression schemes. Based upon Goodrich's separator decomposition for planar graphs and Djidjev and Venkatesan's planarizers for bounded-genus graphs, we give an optimal compression scheme for any hereditary (i.e., closed under taking subgraphs) class G under the premise that any n-node graph of G to be encoded comes with a genus-o(n2 n) embedding. By Mohar's linear-time algorithm that embeds a bounded-genus graph on a genus-O(1) surface, our result implies that any hereditary class of genus-O(1) graphs admits an optimal compression scheme. For instance, our result yields the first-known optimal compression schemes for planar graphs, plane graphs, graphs embedded on genus-1 surfaces, graphs with genus 2 or less, 3-colorable directed plane graphs, 4-outerplanar graphs, and forests with degree at most 5. For non-hereditary graph classes, we also give a methodology for obtaining optimal compression schemes. From this methodology, we give the first known optimal compression schemes for triangulations of genus-O(1) surfaces and floorplans.
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