Near-optimal adjacency labeling scheme for power-law graphs
Distributed, Parallel, and Cluster Computing
2015-02-16 v1 Data Structures and Algorithms
Abstract
An adjacency labeling scheme is a method that assigns labels to the vertices of a graph such that adjacency between vertices can be inferred directly from the assigned label, without using a centralized data structure. We devise adjacency labeling schemes for the family of power-law graphs. This family that has been used to model many types of networks, e.g. the Internet AS-level graph. Furthermore, we prove an almost matching lower bound for this family. We also provide an asymptotically near- optimal labeling scheme for sparse graphs. Finally, we validate the efficiency of our labeling scheme by an experimental evaluation using both synthetic data and real-world networks of up to hundreds of thousands of vertices.
Keywords
Cite
@article{arxiv.1502.03971,
title = {Near-optimal adjacency labeling scheme for power-law graphs},
author = {Casper Petersen and Noy Rotbart and Jakob Grue Simonsen and Christian Wulff-Nilsen},
journal= {arXiv preprint arXiv:1502.03971},
year = {2015}
}