tutorial

Developing services in a service oriented architecture for evolutionary algorithms

Authors:

Pablo García-Sánchez,

María Isabel García Arenas,

Antonio Miguel Mora,

Pedro Ángel Castillo,

Carlos Fernandes,

Paloma de las Cuevas,

Gustavo Romero,

Jesús González,

Juan Julián MereloAuthors Info & Claims

GECCO '13 Companion: Proceedings of the 15th annual conference companion on Genetic and evolutionary computation

Pages 1341 - 1348

https://doi.org/10.1145/2464576.2466806

Published: 06 July 2013 Publication History

Abstract

This paper shows the design and implementation of services for Evolutionary Computation following the Service Oriented Architecture paradigm. This paradigm allows independence over language and distribution mechanism. This development is challenging because some technological and design issues, such as abstract design or unordered execution. To solve them, OSGiLiath, an implementation of an abstract Service Oriented Architecture for Evolutionary Algorithms, is used to develop new interoperable services taking into account these restrictions.

References

[1]

E. Alba, F. Almeida, M. Blesa, C. Cotta, M. Díaz, I. Dorta, J. Gabarró, C. León, G. Luque, J. Petit, C. Rodríguez, A. Rojas, and F. Xhafa. Efficient parallel LAN/WAN algorithms for optimization. the MALLBA project. Parallel Computing, 32(5-6):415--440, 2006.

Digital Library

[2]

J. Alcalá-Fdez, L. Sánchez, S. García, M. J. del Jesús, S. Ventura, J. M. Garrell i Guiu, J. Otero, C. Romero, J. Bacardit, V. M. Rivas, J. C. Fernández, and F. Herrera. KEEL: a software tool to assess evolutionary algorithms for data mining problems. Soft Computing, 13(3):307--318, 2009.

Digital Library

[3]

M. Altunay, P. Avery, K. Blackburn, B. Bockelman, M. Ernst, D. Fraser, R. Quick, R. Gardner, S. Goasguen, T. Levshina, M. Livny, J. McGee, D. Olson, R. Pordes, M. Potekhin, A. Rana, A. Roy, C. Sehgal, I. Sfiligoi, F. Wuerthwein, and Open Sci Grid Executive Board. A Science Driven Production Cyberinfrastructure-the Open Science Grid. Journal of GRID Computing, 9(2, Sp. Iss. SI):201--218, JUN 2011.

Digital Library

[4]

M.G. Arenas, Pierre Collet, A.E. Eiben, Márk Jelasity, J. J. Merelo, Ben Paechter, Mike Preuß, and Marc Schoenauer. A framework for distributed evolutionary algorithms. In Parallel Problem Solving from Nature, PPSN VII, pages 665--675, 2002.

Digital Library

[5]

J. J. Durillo, A. J. Nebro, and E. Alba. The jmetal framework for multi-objective optimization: Design and architecture. In IEEE Congress on Evolutionary Computation, pages 1--8, 2010.

[6]

C. Gagné and M. Parizeau. Genericity in evolutionary computation software tools: Principles and case-study. International Journal on Artificial Intelligence Tools, 15(2):173, 2006.

[7]

P. García-Sánchez, J. González, P. Castillo, J. Merelo, A. Mora, J. Laredo, and M. Arenas. A Distributed Service Oriented Framework for Metaheuristics Using a Public Standard. Nature Inspired Cooperative Strategies for Optimization (NICSO 2010), pages 211--222, 2010.

[8]

P. García-Sánchez, J. González, P.A. Castillo, M.G. Arenas, and J.J. Merelo-Guervós. Service oriented evolutionary algorithms. Soft Computing, pages 1--17, 2013. In press.

[9]

P. García-Sánchez, J. González, A. Miguel Mora, and A. Prieto. Deploying intelligent e-health services in a mobile gateway. Expert Syst. Appl., 40(4):1231--1239, 2013.

Digital Library

[10]

L.D. Gaspero and A. Schaerf. Easylocal++: an object-oriented framework for the flexible desgin of local search algorithms and metaheuristics. In Proceedings of 4th Metaheuristics International Conference (MIC'2001), pages 287--292, 2001.

[11]

J. R. González, D. A. Pelta, and A. D. Masegosa. A framework for developing optimization-based decision support systems. Expert Systems with Applications, 36(3, Part 1):4581--4588, 2009.

Digital Library

[12]

P. Kriens. Research challenges for OSGi. 2008. Available at: http://www.osgi.org/blog/2008/02/research-challenges-for-osgi.html.

[13]

C. León, G. Miranda, and C. Segura. Metco: A parallel plugin-based framework for multi-objective optimization. International Journal on Artificial Intelligence Tools, 18(4):569--588, 2009.

[14]

A. Liefooghe, L. Jourdan, and E.G. Talbi. A software framework based on a conceptual unified model for evolutionary multiobjective optimization: ParadisEO-MOEO. European Journal of Operational Research, 2010.

[15]

S. Luke et al. ECJ: A Java-based Evolutionary Computation and Genetic Programming Research System, 2009. Available at http://www.cs.umd.edu/projects/plus/ec/ecj.

[16]

J.J. Merelo Guervós, P. Castillo, and E. Alba. Algorithm::evolutionary, a flexible Perl module for evolutionary computation. Soft Computing - A Fusion of Foundations, Methodologies and Applications, 14:1091--1109, 2010.

Digital Library

[17]

A. Munawar, M. Wahib, M. Munetomo, and K. Akama. The design, usage, and performance of gridufo: A grid based unified framework for optimization. Future Generation Computer Systems, 26(4):633--644, 2010.

Digital Library

[18]

OSGi Alliance. OSGi service platform release 4.2, 2010. Available at: http://www.osgi.org/Release4/Download.

[19]

M. Papazoglou and W.-J. van den Heuvel. Service oriented architectures: approaches, technologies and research issues. The VLDB Journal, 16:389--415, 2007. 10.1007/s00778-007-0044-3.

Digital Library

[20]

M. Petzold, O. Ullrich, and E. Speckenmeyer. Dynamic distributed simulation of DEVS models on the OSGi service platform. Proceedings of ASIM 2011, 2011.

[21]

S. Wagner and M. Affenzeller. HeuristicLab: A generic and extensible optimization environment. In Ribeiro, B. and Albrecht, R. F. and Dobnikar, A. and Pearson, D. W. and Steele, N. C., editor, Adaptive and Natural Computing Algorithms, Springer Computer Science, pages 538--541, 2005. 7th International Conference on Adaptive and Natural Computing Algorithms (ICANNGA), Coimbra, Portugal, MAR 21--23, 2005.

[22]

S. Wagner, S. Winkler, E. Pitzer, G. Kronberger, A. Beham, R. Braune, and M. Affenzeller. Benefits of plugin-based heuristic optimization software systems. In Roberto Moreno Díaz, Franz Pichler, and Alexis Quesada Arencibia, editors, Computer Aided Systems Theory - EUROCAST 2007, volume 4739 of Lecture Notes in Computer Science, pages 747--754. Springer Berlin / Heidelberg, 2007.

Digital Library

[23]

B. M. Wall. A genetic algorithm for resource-constrained scheduling, Ph.D. thesis, MIT. 1996. Available at: http://lancet.mit.edu/ga.

Digital Library

Cited By

França Jda Costa Junior ASoares M(2020)Architecture-Driven Development of an Electronic Health Record Considering the SOAQM Quality ModelSN Computer Science10.1007/s42979-020-00150-x1:3Online publication date: 25-Apr-2020
https://dl.acm.org/doi/10.1007/s42979-020-00150-x
Soares MM. S. França J(2016)Characterization of the Application of Service-Oriented Design Principles in Practice: A Systematic Literature ReviewJournal of Software10.17706/jsw.11.4.403-41711:5(403-417)Online publication date: 2016
https://doi.org/10.17706/jsw.11.4.403-417
Rodriguez LDiosa HRojas-Galeano S(2014)Towards a component-based software architecture for genetic algorithms2014 9th Computing Colombian Conference (9CCC)10.1109/ColumbianCC.2014.6955331(1-6)Online publication date: Sep-2014
https://doi.org/10.1109/ColumbianCC.2014.6955331

Index Terms

Developing services in a service oriented architecture for evolutionary algorithms
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies
      1. Heuristic function construction
2. Software and its engineering

Recommendations

Automatic service composition with heterogeneous service-oriented architectures
ICOST'10: Proceedings of the Aging friendly technology for health and independence, and 8th international conference on Smart homes and health telematics

Service-Oriented Architecture is widely used to program pervasive spaces such as Smart Homes because of its capabilities to handle dynamic and heterogeneous environments. It is often the case that the services required are designed and implemented using ...
Service oriented evolutionary algorithms

This work presents a service oriented architecture for evolutionary algorithms, and an implementation of this architecture using a specific technology (called OSGiLiath). Service oriented architecture is a computational paradigm where users interact ...
Complex Services Availability in Service Oriented Systems
ICSENG '11: Proceedings of the 2011 21st International Conference on Systems Engineering

The aim of the paper is to discuss some issues related to services composition in service oriented systems based on Service Oriented Architecture (SOA) paradigm. The main feature of service oriented architecture is that the required services may be ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

GECCO '13 Companion: Proceedings of the 15th annual conference companion on Genetic and evolutionary computation

July 2013

1798 pages

ISBN:9781450319645

DOI:10.1145/2464576

Editor:
Christian Blum
IKERBASQUE and University of the Basque Country UPV/EHU, Spain
,
General Chair:
Enrique Alba
University of Malaga, Spain

Copyright © 2013 ACM.

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]

Sponsors

SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 July 2013

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Tutorial

Conference

GECCO '13

Sponsor:

SIGEVO

GECCO '13: Genetic and Evolutionary Computation Conference

July 6 - 10, 2013

Amsterdam, The Netherlands

Acceptance Rates

Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
122
Total Downloads

Downloads (Last 12 months)3
Downloads (Last 6 weeks)1

Reflects downloads up to 01 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

França Jda Costa Junior ASoares M(2020)Architecture-Driven Development of an Electronic Health Record Considering the SOAQM Quality ModelSN Computer Science10.1007/s42979-020-00150-x1:3Online publication date: 25-Apr-2020
https://dl.acm.org/doi/10.1007/s42979-020-00150-x
Soares MM. S. França J(2016)Characterization of the Application of Service-Oriented Design Principles in Practice: A Systematic Literature ReviewJournal of Software10.17706/jsw.11.4.403-41711:5(403-417)Online publication date: 2016
https://doi.org/10.17706/jsw.11.4.403-417
Rodriguez LDiosa HRojas-Galeano S(2014)Towards a component-based software architecture for genetic algorithms2014 9th Computing Colombian Conference (9CCC)10.1109/ColumbianCC.2014.6955331(1-6)Online publication date: Sep-2014
https://doi.org/10.1109/ColumbianCC.2014.6955331

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten