LI Yifan

PhD graduated
Team : BD
Departure date : 12/31/2017
https://lip6.fr/Yifan.Li

Supervision : CĂ©dric DU MOUZA

Co-supervision : CONSTANTIN Camélia

Edge partitioning of large graphs

In this thesis, we focus on the fundamental problem of graph partitioning, in the context of unexpectedly fast growth of data sources, ranging from social networks to internet of things. Based on the topological properties of real large graphs, e.g. power-law degree distribution, and on recent results which prove that vertex-cut partitioning provides better balanced workload and performances when processing algorithms on graphs, we propose a block-based edge partition method which can efficiently explore the locality underlying graphical structures to enhance the execution of graph algorithm and to reduce the inter-partition communication cost.
Another challenge with large graphs is their high-variety. Most real life graph applications produce heterogenous datasets, in which the vertices and/or edges which may present different types or labels. For this reason, our work is extended to multi-layer graphs with taking into account the edges closeness and labels distribution during partitioning process. Our experiments over real-world datasets demonstrate the good behavior of our proposal.

Defence : 12/15/2017

Jury members :

Prof. PUCHERAL Philippe, SMIS, UVSQ [Rapporteur]
Prof. VODISLAV Dan, ETIS, Univ. Cergy-Pontoise [Rapporteur]
Prof. AMANN Bernd, Lip6, UPMC
Prof. COHEN Sarah, LRI, Univ. Paris-Sud
Dr. CONSTANTIN Camelia, Lip6, UPMC
Dr. DU MOUZA Cedric, CEDRIC, CNAM

Departure date : 12/31/2017

2015-2019 Publications

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