S. Aridhi and E. Mephu-nguifo, Big Graph Mining: Frameworks and Techniques, Big Data Research, vol.6, pp.1-10, 2016.
DOI : 10.1016/j.bdr.2016.07.002
URL : http://arxiv.org/pdf/1602.03072

S. Aridhi, A. Montresor, and Y. Velegrakis, BLADYG: A Graph Processing Framework for Large Dynamic Graphs, Big Data Research, vol.9, pp.9-17, 2017.
DOI : 10.1016/j.bdr.2017.05.003
URL : https://hal.archives-ouvertes.fr/hal-01577882

T. G. Armstrong, V. Ponnekanti, D. Borthakur, and M. Callaghan, LinkBench, Proceedings of the 2013 international conference on Management of data, SIGMOD '13, pp.1185-1196, 2013.
DOI : 10.1145/2463676.2465296

S. Candau, J. Bastide, and M. Delsanti, Structural, elastic, and dynamic properties of swollen polymer networks, Polymer Networks, pp.27-71, 1982.
DOI : 10.1007/3-540-11471-8_2

J. Dean and S. Ghemawat, MapReduce, Communications of the ACM, vol.51, issue.1, pp.107-113, 2008.
DOI : 10.1145/1327452.1327492

W. Dhifli, S. Aridhi, and E. M. Nguifo, MR-SimLab: Scalable subgraph selection with label similarity for big data, Information Systems, vol.69, pp.155-163, 2017.
DOI : 10.1016/j.is.2017.05.006
URL : https://hal.archives-ouvertes.fr/hal-01573398

B. Elser and A. Montresor, An evaluation study of BigData frameworks for graph processing, 2013 IEEE International Conference on Big Data, pp.60-67, 2013.
DOI : 10.1109/BigData.2013.6691555

J. E. Gonzalez, Y. Low, H. Gu, D. Bickson, and C. Guestrin, Powergraph: Distributed graph-parallel computation on natural graphs, In: OSDI, vol.12, p.2, 2012.

B. Han, L. Liu, and E. Omiecinski, NEAT: Road Network Aware Trajectory Clustering, 2012 IEEE 32nd International Conference on Distributed Computing Systems, pp.142-151, 2012.
DOI : 10.1109/ICDCS.2012.31
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.228.1672

C. Intanagonwiwat, R. Govindan, and D. Estrin, Directed diffusion, Proceedings of the 6th annual international conference on Mobile computing and networking , MobiCom '00, pp.56-67, 2000.
DOI : 10.1145/345910.345920

J. Kreps, N. Narkhede, and J. Rao, Kafka: A distributed messaging system for log processing, Proceedings of the NetDB, pp.1-7, 2011.

P. Lee, L. V. Lakshmanan, and E. E. Milios, Incremental cluster evolution tracking from highly dynamic network data, 2014 IEEE 30th International Conference on Data Engineering, pp.3-14, 2014.
DOI : 10.1109/ICDE.2014.6816635

X. Li, J. Han, J. G. Lee, and H. Gonzalez, Traffic density-based discovery of hot routes in road networks Advances in Spatial and Temporal Databases pp, pp.441-459, 2007.

R. P. Magalhães, G. Coutinho, J. Macêdo, C. Ferreira, L. Cruz et al., Graphast, Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS '15, p.93, 2015.
DOI : 10.1016/B978-012722442-8/50076-8

G. Malewicz, M. H. Austern, A. J. Bik, J. C. Dehnert, I. Horn et al., Pregel: a system for large-scale graph processing, Proceedings of the 2010 ACM SIGMOD International Conference on Management of data, pp.135-146, 2010.

S. Moon, J. G. Lee, M. Kang, M. Choy, and J. W. Lee, Parallel community detection on large graphs with MapReduce and GraphChi, Data & Knowledge Engineering, vol.104, pp.17-31, 2016.
DOI : 10.1016/j.datak.2015.05.001

A. Roy, I. Mihailovic, and W. Zwaenepoel, X-Stream, Proceedings of the Twenty-Fourth ACM Symposium on Operating Systems Principles, SOSP '13, pp.472-488, 2013.
DOI : 10.1145/2517349.2522740

C. Scholliers, ´. E. Tanter, and W. De-meuter, Parallel actor monitors: Disentangling task-level parallelism from data partitioning in the actor model, Science of Computer Programming, vol.80, pp.52-64, 2014.
DOI : 10.1016/j.scico.2013.03.011

D. Sengupta, N. Sundaram, X. Zhu, T. L. Willke, J. Young et al., GraphIn: An Online High Performance Incremental Graph Processing Framework, pp.319-333, 2016.
DOI : 10.1145/1519065.1519089