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Multimodal pattern-oriented software architecture for self-optimization and self-configuration in autonomic computing system using multi objective evolutionary algorithms

Published:03 August 2012Publication History

ABSTRACT

Current autonomic computing systems are ad hoc solutions that are designed and implemented from the scratch, and there are no universal standard (or well established) software methodologies to develop. There are also significant limitations to the way in which these systems are validated. When designing software, in most cases two or more patterns are to be composed to solve a bigger problem. A composite design patterns shows a synergy that makes the composition more than just the sum of its parts which leads to ready-made software architectures. As far as we know, there are no studies on composition of design patterns and pattern languages for autonomic computing domain.In this paper we propose multimodal pattern-oriented software architecture for self-optimization and self-configuration in autonomic computing system using design patterns composition, multi objective evolutionary algorithms, and service oriented architecture (SOA) that software designers and/or programmers can exploit to drive their work. We evaluate the effectiveness of our architecture with and without design patterns compositions. The use of composite design patterns in the architecture and quantitative measurements are presented. A simple UML class diagram is used to describe the architecture.

References

  1. Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley Professional Computing Series. Pearson Education, 2004.Google ScholarGoogle Scholar
  2. N. Burns, M. Bradley, and M.-L. Liu. Applying design patterns in distributing a genetic algorithm application. In Software Engineering Research and Practice, pages 154--160, 2005.Google ScholarGoogle Scholar
  3. N. Cacho, C. Sant'Anna, E. Figueiredo, A. Garcia, T. Batista, and C. Lucena. Composing design patterns: a scalability study of aspect-oriented programming. In Proceedings of the 5th international conference on Aspect-oriented software development, pages 109--121. ACM, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. P. Dazzi, F. Nidito, and M. Pasquali. New perspectives in autonomic design patterns for stream-classification-systems. In Proceedings of the 2007 workshop on Automating service quality: Held at the International Conference on Automated Software Engineering (ASE), WRASQ '07, pages 34--37, New York, NY, USA, 2007. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. J. Dong. Uml extensions for design pattern compositions. Journal of object technology, 1(5):151--163, 2002.Google ScholarGoogle Scholar
  6. J. Dong, Y. Zhao, and Y. Sun. A matrix-based approach to recovering design patterns. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 39(6):1271--1282, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. T. Eze, R. Anthony, A. Soper, and C. Walshaw. A technique for measuring the level of autonomicity of self-managing systems. In ICAS 2012, The Eighth International Conference on Autonomic and Autonomous Systems, pages 8--13, 2012.Google ScholarGoogle Scholar
  8. J. O. Hallstrom, A. R. Dalton, and N. Soundarajan. Parallel monitoring of design pattern contracts. In SEKE, pages 236--241, 2006.Google ScholarGoogle Scholar
  9. M. Harman, P. McMinn, J. de Souza, and S. Yoo. Search based software engineering: Techniques, taxonomy, tutorial. Empirical Software Engineering and Verification, pages 1--59, 2012. Google ScholarGoogle ScholarCross RefCross Ref
  10. M. Huebscher and J. McCann. A survey of autonomic computing--degrees, models, and applications. ACM Comput. Surv, 40(3):1--28, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. B. Huston. The effects of design pattern application on metric scores. Journal of Systems and Software, 58(3):261--269, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. R. Lincke, J. Lundberg, and W. Löwe. Comparing software metrics tools. In Proceedings of the 2008 international symposium on Software testing and analysis, pages 131--142. ACM, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. V. Mannava and T. Ramesh. An adaptive design pattern for genetic algorithm-based composition of web services in autonomic computing systems using soa. In R. Li, J. Cao, and J. Bourgeois, editors, Advances in Grid and Pervasive Computing, volume 7296 of Lecture Notes in Computer Science, pages 98--108. Springer Berlin/Heidelberg, 2012. 10.1007/978-3-642-30767-6_9. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. V. Mannava and T. Ramesh. A novel adaptive re-configuration compliance design pattern for autonomic computing systems. Procedia Engineering, 30(0):1129--1137, 2012. <ce:title>International Conference on Communication Technology and System Design 2011</ce:title>.Google ScholarGoogle ScholarCross RefCross Ref
  15. J. McCann and M. Huebscher. Evaluation issues in autonomic computing. In Grid and Cooperative Computing-GCC 2004 Workshops, pages 597--608. Springer, 2004.Google ScholarGoogle ScholarCross RefCross Ref
  16. M. Mucientes, M. Lama, and M. Couto. A genetic programming-based algorithm for composing web services. In Intelligent Systems Design and Applications, 2009. ISDA'09. Ninth International Conference on, pages 379--384. IEEE, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. B. Naga Srinivas Repuri, V. Mannava, and T. Ramesh. An adaptive design pattern for genetic algorithm based autonomic computing system. In D. C. Wyld, J. Zizka, and D. Nagamalai, editors, Advances in Computer Science, Engineering and Applications, volume 166 of Advances in Intelligent and Soft Computing, pages 273--282. Springer Berlin/Heidelberg, 2012. 10.1007/978-3-642-30157-5_28.Google ScholarGoogle Scholar
  18. M. Rahman, R. Ranjan, R. Buyya, and B. Benatallah. A taxonomy and survey on autonomic management of applications in grid computing environments. Concurrency and Computation: Practice and Experience, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. A. J. Ramirez and B. H. C. Cheng. Design patterns for developing dynamically adaptive systems. In Proceedings of the 2010 ICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems, SEAMS '10, pages 49--58, New York, NY, USA, 2010. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. H. Shuaib, R. Anthony, and M. Pelc. A framework for certifying autonomic computing systems. In ICAS 2011, The Seventh International Conference on Autonomic and Autonomous Systems, pages 122--127, 2011.Google ScholarGoogle Scholar
  21. T. Taibi. Formalizing design patterns composition. the IEE-Proceeding Software, 153(3):127--136, 2006.Google ScholarGoogle Scholar
  22. S. M. Yacoub and H. H. Ammar. Uml support for designing software systems as a composition of design patterns. In Proceedings of the International Conference on Unified Modeling Language, pages 149--165. Springer-Verlag, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. W. Zimmer et al. Relationships between design patterns. Pattern languages of program design, 1:345--364, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library

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                cover image ACM Other conferences
                ICACCI '12: Proceedings of the International Conference on Advances in Computing, Communications and Informatics
                August 2012
                1307 pages
                ISBN:9781450311960
                DOI:10.1145/2345396

                Copyright © 2012 ACM

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                Publication History

                • Published: 3 August 2012

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