@inproceedings{9b42d122bbef4c77b2a58357453d84d4,
title = "RealGraph: A graph engine leveraging the power-law distribution of real-world graphs",
abstract = "As the size of real-world graphs has drastically increased in recent years, a wide variety of graph engines have been developed to deal with such big graphs efficiently. However, the majority of graph engines have been designed without considering the power-law degree distribution of real-world graphs seriously. Two problems have been observed when existing graph engines process real-world graphs: inefficient scanning of the sparse indicator and the delay in iteration progress due to uneven workload distribution. In this paper, we propose RealGraph, a single-machine based graph engine equipped with the hierarchical indicator and the block-based workload allocation. Experimental results on real-world datasets show that RealGraph significantly outperforms existing graph engines in terms of both speed and scalability.",
author = "Jo, {Yong Yeon} and Kim, {Sang Wook} and Jang, {Myung Hwan} and Park, {Sun Ju}",
year = "2019",
month = may,
day = "13",
doi = "10.1145/3308558.3313434",
language = "English",
series = "The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019",
publisher = "Association for Computing Machinery, Inc",
pages = "807--817",
booktitle = "The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019",
note = "2019 World Wide Web Conference, WWW 2019 ; Conference date: 13-05-2019 Through 17-05-2019",
}