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A parallel genetic algorithms framework based on Hadoop MapReduce

Published: 13 April 2015 Publication History

Abstract

This paper describes a framework for developing parallel Genetic Algorithms (GAs) on the Hadoop platform, following the paradigm of MapReduce. The framework allows developers to focus on the aspects of GA that are specific to the problem to be addressed. Using the framework a GA application has been devised to address the Feature Subset Selection problem. A preliminary performance analysis showed promising results.

References

[1]
D. Cutting. Data interoperability with apache avro. Cloudera Blog, 2011.
[2]
L. Di Geronimo, F. Ferrucci, A. Murolo, and F. Sarro. A parallel genetic algorithm based on hadoop mapreduce for the automatic generation of junit test suites. In Software Testing, Verification and Validation (ICST), 2012 IEEE 5th International Conference on, pages 785--793. IEEE, 2012.
[3]
S. Di Martino, F. Ferrucci, V. Maggio, and F. Sarro. Towards Migrating Genetic Algorithms for Test Data Generation to the Cloud, chapter 6, pages 113--135. IGI Global, 2012.
[4]
F. Ferrucci, M.-T. Kechadi, P. Salza, and F. Sarro. A framework for genetic algorithms based on hadoop. arXiv preprint arXiv:1312.0086, 2013.
[5]
D. E. Goldberg. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Longman Publishing Co., Inc., 1989.
[6]
M. A. Hall. Correlation-based Feature Selection for Machine Learning. PhD thesis, The University of Waikato, 1999.
[7]
M. Harman and B. F. Jones. Search-based software engineering. Information and Software Technology, 43(14):833--839, 2001.
[8]
C. Jin, C. Vecchiola, and R. Buyya. Mrpga: An extension of mapreduce for parallelizing genetic algorithms. In E-Science (e-Science), 2008 IEEE 4th International Conference on, pages 214--221. IEEE, 2008.
[9]
F. Sarro, S. Di Martino, F. Ferrucci, and C. Gravino. A further analysis on the use of genetic algorithm to configure support vector machines for inter-release fault prediction. In Applied Computing (SAC), 2012 ACM 27th Symposium on, pages 1215--1220. ACM, 2012.
[10]
F. Sarro, F. Ferrucci, and C. Gravino. Single and multi objective genetic programming for software development effort estimation. In Applied Computing (SAC), 2012 ACM 27th Symposium on, pages 1221--1226. ACM, 2012.
[11]
A. Verma, X. Llorà, D. E. Goldberg, and R. H. Campbell. Scaling genetic algorithms using mapreduce. In Intelligent Systems Design and Applications (ISDA), 2009 9th International Conference on, pages 13--18. IEEE, 2009.
[12]
T. White. Hadoop: The Definitive Guide. O'Reiily, third edition, 2012.

Cited By

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  • (2022)Distributed Evolutionary Feature Selection for Big Data ProcessingVietnam Journal of Computer Science10.1142/S219688882250015409:03(313-332)Online publication date: 17-Mar-2022
  • (2022)Sentinel: A Hyper-Heuristic for the Generation of Mutant Reduction StrategiesIEEE Transactions on Software Engineering10.1109/TSE.2020.300249648:3(803-818)Online publication date: 1-Mar-2022
  • (2022)Memristor Parallel Computing for a Matrix-Friendly Genetic AlgorithmIEEE Transactions on Evolutionary Computation10.1109/TEVC.2022.314441926:5(901-910)Online publication date: Oct-2022
  • Show More Cited By

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cover image ACM Conferences
SAC '15: Proceedings of the 30th Annual ACM Symposium on Applied Computing
April 2015
2418 pages
ISBN:9781450331968
DOI:10.1145/2695664
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 13 April 2015

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Author Tags

  1. MapReduce
  2. hadoop
  3. parallel genetic algorithms

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  • Short-paper

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SAC 2015
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SAC 2015: Symposium on Applied Computing
April 13 - 17, 2015
Salamanca, Spain

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SAC '15 Paper Acceptance Rate 291 of 1,211 submissions, 24%;
Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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The 40th ACM/SIGAPP Symposium on Applied Computing
March 31 - April 4, 2025
Catania , Italy

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Cited By

View all
  • (2022)Distributed Evolutionary Feature Selection for Big Data ProcessingVietnam Journal of Computer Science10.1142/S219688882250015409:03(313-332)Online publication date: 17-Mar-2022
  • (2022)Sentinel: A Hyper-Heuristic for the Generation of Mutant Reduction StrategiesIEEE Transactions on Software Engineering10.1109/TSE.2020.300249648:3(803-818)Online publication date: 1-Mar-2022
  • (2022)Memristor Parallel Computing for a Matrix-Friendly Genetic AlgorithmIEEE Transactions on Evolutionary Computation10.1109/TEVC.2022.314441926:5(901-910)Online publication date: Oct-2022
  • (2021)Spark-ITGO: a parallel invasive tumor growth optimization algorithm on sparkCluster Computing10.1007/s10586-021-03396-z25:4(2633-2660)Online publication date: 30-Aug-2021
  • (2019)A Comprehensive Survey on Cloud Data Mining (CDM) Frameworks and AlgorithmsACM Computing Surveys10.1145/334926552:5(1-62)Online publication date: 13-Sep-2019
  • (2019)Speed up genetic algorithms in the cloud using software containersFuture Generation Computer Systems10.1016/j.future.2018.09.06692(276-289)Online publication date: Mar-2019
  • (2018)Improved Iteration FCM Algorithm for MapReduce ResearchProceedings of the 2nd International Conference on Telecommunications and Communication Engineering10.1145/3291842.3291889(379-383)Online publication date: 28-Nov-2018
  • (2018)Feature Selection Using Genetic Algorithm for Big DataThe International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018)10.1007/978-3-319-74690-6_35(352-361)Online publication date: 26-Jan-2018
  • (2017)Using Hadoop MapReduce for Parallel Genetic Algorithms: A Comparison of the Global, Grid and Island ModelsEvolutionary Computation10.1162/evco_a_00213(1-33)Online publication date: 29-Jun-2017
  • (2016)elephant56Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion10.1145/2908961.2931722(1315-1322)Online publication date: 20-Jul-2016
  • Show More Cited By

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