Abstract
Self-adaptive systems research is expanding as systems professionals recognize the importance of automation for managing the growing complexity, scale, and scope of software systems. The current approach to designing such systems is ad hoc, varied, and fractured, often resulting in systems with parts of multiple, sometimes poorly compatible designs. In addition to the challenges inherent to all software, this makes evaluating, understanding, comparing, maintaining, and even using such systems more difficult. This paper discusses the importance of systematic design and identifies the dimensions of the self-adaptive system design space. It identifies key design decisions, questions, and possible answers relevant to the design space, and organizes these into five clusters: observation, representation, control, identification, and enacting adaptation. This characterization can serve as a standard lexicon, that, in turn, can aid in describing and evaluating the behavior of existing and new self-adaptive systems. The paper also outlines the future challenges for improving the design of self-adaptive systems.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Andersson, J., de Lemos, R., Malek, S., Weyns, D.: Modeling Dimensions of Self-Adaptive Software Systems. In: Cheng, B.H.C., de Lemos, R., Giese, H., Inverardi, P., Magee, J. (eds.) Self-Adaptive Systems. LNCS, vol. 5525, pp. 27–47. Springer, Heidelberg (2009)
Brake, N., Cordy, J.R., Dancy, E., Litoiu, M., Popescu, V.: Automating discovery of software tuning parameters. In: Proceedings of the 3rd International Workshop on Software Engineering for Adaptive and Self-Managing Systems, Leipzig, Germany, pp. 65–72 (2008)
Brooks Jr., F.P.: The Design of Design: Essays from a Computer Scientist. Addison-Wesley, New York (2010)
Brun, Y., Di Marzo Serugendo, G., Gacek, C., Giese, H., Kienle, H., Litoiu, M., Müller, H., Pezzè, M., Shaw, M.: Engineering Self-Adaptive Systems through Feedback Loops. In: Cheng, B.H.C., de Lemos, R., Giese, H., Inverardi, P., Magee, J. (eds.) Self-Adaptive Systems. LNCS, vol. 5525, pp. 48–70. Springer, Heidelberg (2009)
Buschmann, F., Henney, K., Schmidt, D.: Pattern-oriented software architecture: On patterns and pattern languages, vol. 5. John Wiley & Sons Inc. (2007)
Checiu, L., Solomon, B., Ionescu, D., Litoiu, M., Iszlai, G.: Observability and controllability of autonomic computing systems for composed web services. In: Proceedings of the 6th IEEE International Symposium on Applied Computational Intelligence and Informatics, pp. 269–274 (2011)
Dobson, S., Denazis, S., Fernández, A., Gaïti, D., Gelenbe, E., Massacci, F., Nixon, P., Saffre, F., Schmidt, N., Zambonelli, F.: A survey of autonomic communications. ACM Transactions on Autonomous and Adaptive Systems (TAAS) 1, 223–259 (2006)
Gamma, E., Helm, R., Johnson, R., Vlissides, J.: Design patterns: Elements of reusable object-oriented software. Addison-Wesley Longman Publishing Co., Inc. (1995)
Geihs, K., Reichle, R., Wagner, M., Khan, M.U.: Modeling of Context-Aware Self-Adaptive Applications in Ubiquitous and Service-Oriented Environments. In: Cheng, B.H.C., de Lemos, R., Giese, H., Inverardi, P., Magee, J. (eds.) Self-Adaptive Systems. LNCS, vol. 5525, pp. 146–163. Springer, Heidelberg (2009)
Ghanbari, H., Litoiu, M.: Identifying implicitly declared self-tuning behavior through dynamic analysis. In: Proceedings of the 4th International Workshop on Software Engineering for Adaptive and Self-Managing Systems, Vancouver, BC, Canada, pp. 48–57 (2009)
Hellerstein, J., Diao, Y., Parekh, S., Tilbury, D.: Feedback control of computing systems, pp. 378–384. Wiley Interscience (2004)
IBM: An architectural blueprint for autonomic computing. (June 2006), http://www-01.ibm.com/software/tivoli/autonomic/pdfs/AC_Blueprint_White_Paper_4th.pdf
Kazman, R., Klein, M., Barbacci, M., Longstaff, T., Lipson, H., Carriere, J.: The architecture tradeoff analysis method. In: Proceedings of the 4th IEEE International Conference on Engineering of Complex Computer Systems, pp. 68–78 (1998)
Kephart, J., Chess, D.: The vision of autonomic computing. Computer 36(1), 41–50 (2003)
Kramer, J., Magee, J.: Self-managed systems: an architectural challenge. In: Future of Software Engineering, pp. 259–268 (2007)
Lane, T.G.: Studying software architecture through design spaces and rules. Tech. Rep. CMU/SEI-90-TR-18, Software Engineering Institute, Carnegie Mellon University (November 1990)
Litoiu, M.: Application performance evaluator and resource allocation tool (APERA) (May 2003), http://www.alphaworks.ibm.com/tech/apera
Litoiu, M., Woodside, M., Zheng, T.: Hierarchical model-based autonomic control of software systems. In: Proceedings of the Workshop on Design and Evolution of Autonomic Application Software, St. Louis, MO, USA, pp. 1–7 (2005)
Ramirez, A.J., Cheng, B.H.C.: Design patterns for developing dynamically adaptive systems. In: Proceedings of the 5th International Workshop on Software Engineering for Adaptive and Self-Managing Systems, Cape Town, South Africa, pp. 49–58 (2010)
Shaw, M.: The role of design spaces. IEEE Software (Special Issue on Studying Professional Software Design) 29(1), 46–50 (2012)
Smit, M.: Supporting Quality of Service, Configuration, and Autonomic Reconfiguration using Services-Aware Simulation. Ph.D. thesis, University of Alberta (2011)
Villegas, N.M., Müller, H.A., Tamura, G., Duchien, L., Casallas, R.: A framework for evaluating quality-driven self-adaptive software systems. In: Proceeding of the 6th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, Waikiki, Honolulu, HI, USA, pp. 80–89 (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Brun, Y. et al. (2013). A Design Space for Self-Adaptive Systems. In: de Lemos, R., Giese, H., Müller, H.A., Shaw, M. (eds) Software Engineering for Self-Adaptive Systems II. Lecture Notes in Computer Science, vol 7475. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35813-5_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-35813-5_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35812-8
Online ISBN: 978-3-642-35813-5
eBook Packages: Computer ScienceComputer Science (R0)