2017
Journal article  Open Access

Fast connected components computation in large graphs by vertex pruning

Lulli A., Carlini E., Dazzi P., Lucchese C., Ricci L.

Computational Theory and Mathematics  Settore INF/01 - Informatica  distributed algorithms  Hardware and Architecture  Graph algorithms  Settore ING-INF/05 - Sistemi di Elaborazione delle Informazioni  Distributed computing  Distributed algorithms  graph algorithms  Signal Processing 

Finding connected components is a fundamental task in applications dealing with graph analytics, such as social network analysis, web graph mining and image processing. The exponentially growing size of today's graphs has required the definition of new computational models and algorithms for their efficient processing on highly distributed architectures. In this paper we present CRACKER, an efficient iterative MapReduce-like algorithm to detect connected components in large graphs. The strategy of CRACKER is to transform the input graph in a set of trees, one for each connected component in the graph. Nodes are iteratively removed from the graph and added to the trees, reducing the amount of computation at each iteration. We prove the correctness of the algorithm, evaluate its computational cost and provide an extensive experimental evaluation considering a wide variety of synthetic and real-world graphs. The experimental results show that CRACKER consistently outperforms state-of-the-art approaches both in terms of total computation time and volume of messages exchanged.

Source: IEEE transactions on parallel and distributed systems (Print) 28 (2017): 760–773. doi:10.1109/TPDS.2016.2591038

Publisher: Institute of Electrical and Electronics Engineers,, New York, NY , Stati Uniti d'America


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BibTeX entry
@article{oai:it.cnr:prodotti:366235,
	title = {Fast connected components computation in large graphs by vertex pruning},
	author = {Lulli A. and Carlini E. and Dazzi P. and Lucchese C. and Ricci L.},
	publisher = {Institute of Electrical and Electronics Engineers,, New York, NY , Stati Uniti d'America},
	doi = {10.1109/tpds.2016.2591038},
	journal = {IEEE transactions on parallel and distributed systems (Print)},
	volume = {28},
	pages = {760–773},
	year = {2017}
}