The real world is full of graphs. There are graphs hidden in the friendship relationships between people, in economic transactions, between strangers encountering each other in the streets, in the way gossip spreads through the people, and so on. Few years ago we know they were there, but we were not able to analyze them because the lack of data. Nowadays, however, most of the human activities are mediated by some electronic device, so large datasets describing these graphs have started to become available.
Analyzing these datasets could be difficult. Sometimes they are too large, sometimes they are distributed by nature. We have published several papers about this subject, that can be categorized in the following areas:
- Distributed algorithms for computing properties of graphs [TPDS13] [DEBS16] [DBSDA16]
- Evaluation of big data frameworks [BigData13]
- Distributed frameworks for distributed graph analysis [EuroPar15] [HPGP16] [CBDCom16] [IDEAS16]
[TPDS13] Alberto Montresor, Francesco de Pellegrini, and Daniele Miorandi. Distributed k-core decomposition. IEEE Trans. Parallel Distrib. Syst., 24 (2):288–300, 2013. [PDF], [Bibtex].
[BigData13] Benedikt Elser and Alberto Montresor. An evaluation study of BigData frameworks for graph processing. In Proc. of the 2013 IEEE International Conference on Big Data, BigData’13, pages 60–67. IEEE, Santa Clara, CA, USA, October 2013. ISBN 978–1‑4799–1292‑6. [PDF], [Bibtex].
[EuroPar15] Alessio Guerrieri and Alberto Montresor. DFEP: Distributed funding-based edge partitioning. In Proc. of the 21th International Conference on Parallel Processing, EuroPar’15. Springer, 2015. [PDF], [Bibtex].
[HPGP16] Sabeur Aridhi, Alberto Montresor, and Yannis Velegrakis. BLADYG: A novel block-centric framework for the analysis of large dynamic graphs. In Proceedings of the ACM Workshop on High Performance Graph Processing, HPGP@HPDC 2016, pages 39–42. ACM, Kyoto, Japan, May 2016. [PDF], [Bibtex].
[DEBS16] Sabeur Aridhi, Martin Brugnara, Yannis Velegrakis, and Alberto Montresor. Distributed k-core decomposition and maintenance in large dynamic graphs. In Proc. of the 10th ACM International Conference on Distributed and Event-Based Systems, DEBS’16. ACM, Irvine, CA, June 2016. [PDF], [Bibtex].
[CBDCom16] Alessio Guerrieri, Alberto Montresor, and Simone Centellegher. ETSCH: Partition-centric graph processing. In Proc. of the 1st International Conference on Cloud and Big Data Computing, CBDCom’16. IEEE, Toulouse, France, July 2016. [PDF], [Bibtex].
[IDEAS16] Chayma Sakouhi, Sabeur Aridhi, Alessio Guerrieri, Salma Sassi, and Alberto Montresor1. DynamicDFEP: A distributed edge partitioning approach for large dynamic graphs. In Procedings of the 20th International Database Engineering & Applications Symposium, IDEAS’16. ACM, Montreal, Canada, July 2016. [PDF], [Bibtex].
[DBSDA16] Alessio Guerrieri, Fatemeh Rahimian, Sarunas Girdzijauskas, and Alberto Montresor. Tovel: Distributed graph clustering for word sense disambiguation. In Procedings of the 4th ICDM Workshop on Data Science and Big Data Analytics, DSBDA’16. IEEE, Barcelona, Spain, December 2016. [PDF], [Bibtex].