Toward evolving self-organizing software systems: a complex system point of view
Authors: 
Liguo Yu, David Threm, S. RamaswamyAuthors Info & Claims
Abstract
Complex systems feature a large number of interacting components and as a whole exhibit one or more properties which are not entirely obvious from the properties of individual components. One important property of complex systems is self-organization, which is a process of reorganizing its components or functions to adapt to its environment without being actively guided or managed by an outside source. Complex systems are widely noticeablein many areas, such as physics, chemistry, biology, mechanics, telecommunication, and sociology. In the software engineering field, considerable work has been performed to produce self-adaptive, self-healing, self-optimizing, and selfmanaging systems. In this paper, we attempt to summarize and discuss key properties of complex self-organizing systems (both natural and social) and compare them with similar software systems. Our objective is to provide a unifying perspective for software engineers, enabling themto study nature-inspired engineering as a viable alternative for producing complex, evolving, and self-organizing software systems.
References
[1]
Fromm, J.: The Emergence of Complexity. Kassel University Press (2004).
[2]
Yu, L., Ramaswamy, S.: An Empirical Approach to Evaluating Dependency Locality in Hierarchically Structured Software Systems. J. of Sys. Soft. 82(3), 463-472 (2009).
[3]
Yu, L., Chen, K., Ramaswamy, S.: Multiple-Parameter Coupling Metrics for Layered Component-Based Software. Software Quality Journal 17(1), 5-24 (2009).
[4]
Yu, L., Ramaswamy, S.: Verifying Design Modularity, Hierarchy, and Interaction Locality Using Data Clustering Techniques. In: 45th ACMSE Conf., Winston-Salem, North Carolina, pp. 419-424 (March 2007).
[5]
Simon, H.: The Organization of Complex Systems. In: Hierarchy Theory: The Challenge of Complex Systems. George Braziller, NY (1973).
[6]
Pattee, H.: The Physical Basis and Origin of Hierarchical Control. In: Hierarchy Theory: The Challenge of Complex Systems. George Braziller, NY (1973).
[7]
Simon, H.: The Architecture of Complexity. The Sciences of the Artificial. MIT Press, Cambridge (1969).
[8]
Simon, H.: The Architecture of Complexity: Hierarchic Systems. In: Proceedings of the American Philosophical Society, pp. 467-482 (1962).
[9]
Ramsey, D.: Molecular Coding Problems. New York Academy of Sc., New York (1967).
[10]
Schuster, P.: Evolution in Simple Systems and the Emergence of Complexity. In: Proc.of the 2005 IEEE/WIC/ACM Internl Conf.on Web Intelligence, pp. 33-37 (September 2005).
[11]
Mikulecky, D.: The Emergence of Complexity: Science Coming of Age or Science Growing Old? Computers and Chemistry 25(4), 341-348 (2001).
[12]
Ahl, V., Allen, T.F.H.: Hierarchy Theory, a Vision, Vocabulary and Epistemology. Columbia University Press (1996).
[13]
Whyte, L.L., Wilson, A.G., Wilson, D.: Hierarchical structures. American Elsevier, New York (1969).
[14]
Allen, T.F.H., Starr, T.B.: Hierarchy: Perspectives for Ecological Complexity. University Chicago Press, Chicago (1982).
[15]
Salthe, S.: Evolving Hierarchical Systems: their structure and representation. Columbia University Press, New York (1985).
[16]
O'Neill, R.V., DeAngelis, D., Waide, J., Allen, T.F.H.: A Hierarchical Concept of Ecosystems. Princeton University Press, Princeton (1986).
[17]
Prigogine, I.: End of Certainty. The Free Press, New York (1997).
[18]
Piaget, J.: Genetic Epistemology. W. W. Norton, New York (1971).
[19]
Lane, D.: Hierarchy, Complexity, Society. In: Hierarchy in Natural and Social Sciences, pp. 81-119. Springer, Netherlands (2006).
[20]
Gabaix, X.: Zipf's Law for Cities: An Explanation. Qtrly J. of Econ. 114(3), 739-767 (1999).
[21]
Mei, H., Zhang, L., Yang, F.: A Software Configuration Management Model for Supporting Component-Based Software Development. ACM SIGSOFT Software Engineering Notes 26(2), 53-58 (2001).
[22]
Bruegge, B., Dutoit, A.H.: Object-Oriented Software Engineering Using UML, Patterns, and Java. Pearson Prentice Hall, Upper Saddle River (2004).
[23]
de Jonge, M.: Build-Level Components. IEEE Trans. on S. Engg 31(7), 588-600 (2005).
[24]
Offutt, J., Harrold, M.J., Kolte, P.: A Software Metric System for Module Coupling. Journal of System and Software 20(3), 295-308 (1993).
[25]
Schach, S.R.: Object-Oriented and Classical Software Engineering, 7th edn. McGraw-Hill, New York (2007).
[26]
Ramaswamy, S., Valavanis, K.P.: Modeling, Analysis and Simulation of Failures in a Materials Handling System using Extended Petri Nets. IEEE Transaction on Systems, Man and Cybernetics 24(9), 1358-1373 (1994).
[27]
Garlan, D., Cheng, S.W., Huang, A.C., Schmerl, B.R., Steenkiste, P.: Rainbow: Architecture-Based Self-Adaptation with Reusable Infrastructure. IEEE Computer 37(10), 46-54 (2004).
[28]
Mishra, A., Misra, A.K.: Component Assessment and Proactive Model for Support of Dynamic Integration in Self Adaptive System. ACM SIGSOFT Soft. Engg. Notes 34(4) (2009).
[29]
Geihs, K., Barone, P., Eliassen, F., Floch, J., Fricke, R., Gjorven, E., Hallsteinsen, S., Horn, G., Khan, M.U., Mamelli, A., Papadopoulos, G.A., Paspallis, N., Reichle, R., Stav, E.: A Comprehensive Solution for Application-Level Adaptation. Software Practice and Experience 39(4), 385-422 (2009).
[30]
Vogel, T., Neumann, S., Hildebrandt, S., Giese, H., Becker, B.: Model-Driven Architectural Monitoring and Adaptation for Autonomic Systems. In: Proceedings of the 6th International Conference on Autonomic Computing, Barcelona, Spain, pp. 15-19 (June 2009).
[31]
Bencomo, N.: On the Use of Software Models during Software Execution. In: Proc. of the 2009 ICSE Workshop on Modeling in Software Engg., Canada, pp. 62-67 (2009).
[32]
Krka, I., Edwards, G., Brun, Y., Medvidovic, N.: From System Specifications to Component Behavioral Models. In: Proc. of the New Ideas and Emerging Results Track at the 31st Internl. Conf. on Software Engg., pp. 315-318 (May 2009).
[33]
Abelson, H., Allen, D., Coore, D., Hanson, C., Homsy, G., Thomas, F., Knight, J., Nagpal, R., Rauch, E., Sussman, G.J., Weiss, R.: Amorphous Computing. Comm. of the ACM 43(5), 74-82 (2000).
[34]
Brun, Y., Medvidovic, N.: An Architectural Style for Solving Computationally Intensive Problems on Large Networks. In: Proceedings of 2007 Software Engineering for Adaptive and Self-Managing Systems Workshop at 29th IEEE/ACM International Conference on Software Engineering, Minneapolis, MN, USA (May 2007).
[35]
Di Marzo-Serugendo, G., Fitzgerald, J., Romanovsky, A., Guelfi, N.: A Generic Framework for the Engineering of Self-Adaptive and Self-Organising Systems. Technical Report, School of Computer Science, University of Newcastle, Newcastle, UK (2007).
[36]
Clement, L., Nagpal, R.: Self-Assembly and Self-Repairing Topologies. In: Proc. of the Workshop on Adaptability in Multi-Agent Systems, Sydney, Australia (2003).
[37]
Shen, W.M., Krivokon, M., Chiu, H., Everist, J., Rubenstein, M., Venkatesh, J.: Multimode Locomotion via Superbot Reconfigurable Robots. Autonomous Robots 20(2), 165-177 (2006).
[38]
Yu, L., Ramaswamy, S., Bush, J.: Symbiosis and Software Evolvability. IT Professional 10(4), 56-62 (2008).
Recommendations
Self-organization process in open-source software: An empirical study
Software systems must continually evolve to adapt to new functional requirements or quality requirements to remain competitive in the marketplace. However, different software systems follow different strategies to evolve, affecting both the release plan ...
A systematic review of software architecture evolution research
Context: Software evolvability describes a software system's ability to easily accommodate future changes. It is a fundamental characteristic for making strategic decisions, and increasing economic value of software. For long-lived systems, there is a ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
June 2011
580 pages
ISBN:9783642218262
Sponsors
- Association for the Advancement of Artificial Intelligence
- ACM: Association for Computing Machinery
- INNS: International Neural Network Society
- The European Neural Network Society
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 28 June 2011
Check for updates
Author Tags
Qualifiers
- Article
Conference
IEA/AIE '11
Sponsor:
- ACM
- INNS
IEA/AIE '11: 24th International Conference on Industrial Engineering & Other Applications of Applied Intelligent Systems
June 28 - July 1, 2011
NY, Syracuse
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 28 Sep 2024