Exploiting mean field analysis to model performances of big data architectures

[1]  Maozhen Li,et al.  HSim: A MapReduce simulator in enabling Cloud Computing , 2013, Future Gener. Comput. Syst..

[2]  Mauro Iacono,et al.  The SIMTHESys multiformalism modeling framework , 2012, Comput. Math. Appl..

[3]  Fang-Yie Leu,et al.  PFRF: An adaptive data replication algorithm based on star-topology data grids , 2012, Future Gener. Comput. Syst..

[4]  Lei Yu,et al.  SimMapReduce: A Simulator for Modeling MapReduce Framework , 2011, 2011 Fifth FTRA International Conference on Multimedia and Ubiquitous Engineering.

[5]  Liang Dong,et al.  Starfish: A Self-tuning System for Big Data Analytics , 2011, CIDR.

[6]  Albert G. Greenberg,et al.  Reining in the Outliers in Map-Reduce Clusters using Mantri , 2010, OSDI.

[7]  Maozhen Li,et al.  MRSim: A discrete event based MapReduce simulator , 2010, 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery.

[8]  Rajeev Gandhi,et al.  An Analysis of Traces from a Production MapReduce Cluster , 2010, 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing.

[9]  Rajeev Gandhi,et al.  Kahuna: Problem diagnosis for Mapreduce-based cloud computing environments , 2010, 2010 IEEE Network Operations and Management Symposium - NOMS 2010.

[10]  Gribaudo Marco,et al.  Modeling Biological Pathways: An Object-Oriented like Methodology Based on Mean Field Analysis , 2009, 2009 Third International Conference on Advanced Engineering Computing and Applications in Sciences.

[11]  Mihai Budiu,et al.  Hunting for Problems with Artemis , 2008, WASL.

[12]  Miklós Telek,et al.  Analysis of Large Scale Interacting Systems by Mean Field Method , 2008, 2008 Fifth International Conference on Quantitative Evaluation of Systems.

[13]  M. Benaïm,et al.  A class of mean field interaction models for computer and communication systems , 2008, 2008 6th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks and Workshops.

[14]  Valeria Vittorini,et al.  The OsMoSys approach to multi-formalism modeling of systems , 2004, Software & Systems Modeling.

[15]  Laura Carrington,et al.  A performance prediction framework for scientific applications , 2003, Future Gener. Comput. Syst..

[16]  Fabrizio Petrini,et al.  Predictive Performance and Scalability Modeling of a Large-Scale Application , 2001, ACM/IEEE SC 2001 Conference (SC'01).

[17]  Peter A. Dinda,et al.  An evaluation of linear models for host load prediction , 1999, Proceedings. The Eighth International Symposium on High Performance Distributed Computing (Cat. No.99TH8469).

[18]  Brian Armstrong,et al.  Performance forecasting: towards a methodology for characterizing large computational applications , 1998, Proceedings. 1998 International Conference on Parallel Processing (Cat. No.98EX205).

[19]  Francine Berman,et al.  Performance prediction in production environments , 1998, Proceedings of the First Merged International Parallel Processing Symposium and Symposium on Parallel and Distributed Processing.

[20]  Oscar H. Ibarra,et al.  Adaptive Partitioning and Scheduling for Enhancing WWW Application Performance , 1998, J. Parallel Distributed Comput..

[21]  Anand Sivasubramaniam,et al.  On characterizing bandwidth requirements of parallel applications , 1995, SIGMETRICS '95/PERFORMANCE '95.

[22]  Graham R. Nudd,et al.  A Layered Approach to Parallel Software Performance Prediction: A Case Study , 1994, EUROSIM.

[23]  William H. Press,et al.  Numerical recipes in C++: the art of scientific computing, 2nd Edition (C++ ed., print. is corrected to software version 2.10) , 1994 .

[24]  T. Kurtz Strong approximation theorems for density dependent Markov chains , 1978 .