N. Alon, Y. Matias, and M. Szegedy, The space complexity of approximating the frequency moments, Proceedings of the 28th annual ACM Symposium on Theory of computing (STOC), 1996.

E. Anceaume, Y. Busnel, and B. Sericola, Uniform node sampling service robust against collusions of malicious nodes, 2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2013.
DOI : 10.1109/DSN.2013.6575363

URL : https://hal.archives-ouvertes.fr/hal-00804430

Z. Bar-yossef, T. S. Jayram, R. Kumar, D. Sivakumar, and L. Trevisan, Counting Distinct Elements in a Data Stream, Proceedings of the 6th 0
DOI : 10.1007/3-540-45726-7_1

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.6276

D. Imbalance-?-(-%-)-?, D. Mean, D. Case, D. Wosim-mean, . Wosim-worst et al., Imbalance (?) as a function of ? (? = 0, µ = 2 and k = 10) International Workshop on Randomization and Approximation Techniques (RANDOM), 2002.

L. Breslau, P. Cao, L. Fan, G. Phillips, and S. Shenker, Web caching and Zipf-like distributions: evidence and implications, IEEE INFOCOM '99. Conference on Computer Communications. Proceedings. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. The Future is Now (Cat. No.99CH36320), 1999.
DOI : 10.1109/INFCOM.1999.749260

URL : http://athos.rutgers.edu/~rmartin/teaching/spring02/cs553/readings/breslau99.ps.gz

M. Charikar, K. Chen, and M. Farach-colton, Finding frequent items in data streams, Theoretical Computer Science, vol.312, issue.1, 2004.

P. Flajolet and G. N. Martin, Probabilistic counting algorithms for data base applications, Journal of Computer and System Sciences, vol.31, issue.2, p.31, 1985.
DOI : 10.1016/0022-0000(85)90041-8

URL : https://hal.archives-ouvertes.fr/inria-00076244

B. Gedik, Partitioning functions for stateful data parallelism in stream processing, The VLDB Journal, vol.31, issue.11???16, p.2014
DOI : 10.1007/s00778-013-0335-9

R. L. Graham, Bounds on Multiprocessing Timing Anomalies, SIAM Journal on Applied Mathematics, vol.17, issue.2, 1969.
DOI : 10.1137/0117039

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.90.8131

S. Guha, A. M. Mcgregor-]-d, J. Kane, D. P. Nelson, and . Woodruff, Quantile estimation in random-order streams An optimal algorithm for the distinct element problem, Proceedings of the Symposium on Principles of Databases (PODS), 2009.

R. Kumar, J. Novak, P. Raghavan, and A. Tomkins, On the bursty evolution of blogspace, World Wide Web, vol.8, issue.2, 2005.

A. Metwally, D. Agrawal, and A. Abbadi, Efficient Computation of Frequent and Top-k Elements in Data Streams, Proceedings of the 10th International Conference on Database Theory (ICDT), 2005.
DOI : 10.1007/978-3-540-30570-5_27

. Muthukrishnan, Data Streams: Algorithms and Applications, Foundations and Trends?? in Theoretical Computer Science, vol.1, issue.2, 2005.
DOI : 10.1561/0400000002

URL : http://ce.sharif.edu/courses/90-91/1/ce797-1/resources/root/Data_Streams_-_Algorithms_and_Applications.pdf

M. A. Nasir, G. D. Morales, D. G. Soriano, N. Kourtellis, and M. Serafini, The power of both choices: Practical load balancing for distributed stream processing engines, 2015 IEEE 31st International Conference on Data Engineering, 2015.
DOI : 10.1109/ICDE.2015.7113279

O. Pearce, T. Gamblin, B. R. De-supinski, M. Schulz, and N. M. Amato, Quantifying the effectiveness of load balance algorithms, Proceedings of the 26th ACM international conference on Supercomputing, ICS '12, 2012.
DOI : 10.1145/2304576.2304601