Abstract
Ubiquitous computing (Ubicomp) researchers have been struggling to realize global ubiquitous computing environment (GUCE). Although Ubicomp systems are studied broadly, there are only a few attempts to study Ubicomp systems based on GUCE especially from theories and high-level abstractions models. To bridge the research gap and provide an appropriate theory and model to underlie Ubicomp systems research, this paper describes the Ubicomp systems from socio-technical systems theory and complex adaptive systems theory perspective. This study gives a set of properties for Ubicomp systems as complex adaptive socio-technical systems which is subsequently used to compare three modeling approaches for Ubicomp systems modeling. Three modeling approaches are system dynamics modeling, discrete-even modeling and agent-based modeling respectively. This explorative and comparative study conclude that understanding Ubicomp systems through the complex adaptive socio-technical system theory and modeling Ubicomp systems through agent-based modeling methodology offer insight into the current complexity of Ubicomp systems.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Weiser, M.: The computer for the 21st century. Scientific American 265(3), 94–104 (1991)
Haghnevis, M., Askin, R.G.: A Modeling Framework for Engineered Complex Adaptive Systems. IEEE Systems Journal 6(3), 520–530 (2012)
Ma, J., Yang, L.T.: Towards a smart world and ubiquitous intelligence: a walkthrough from smart things to smart hyperspaces and UbicKids. International Journal of Pervasive Computing and Communications 1(1), 53–68 (2005)
Milner, R.: Ubiquitous computing: shall we understand it? The Computer Journal 49(4), 383–389 (2006)
Kuhn, T.: Using Complexity Science to affect a paradigm shift in Information Systems for the 21st century. Journal of Information Technology 21, 211–215 (2006)
Grus, L., Crompvoets, J.: Spatial data infrastructures as complex adaptive systems. International Journal of Geographical Information Science 24(3), 439–463 (2010)
De Bruijn, H., Herder, P.M.: System and actor perspectives on socio-technical systems. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans 39(5), 981–992 (2009)
Holland, J.: Hidden Order: How Adaptation Builds Complexity. Perseus Books, Massachusetts (1996)
Allen, T.F.H., Starr, T.B.: Hierarchy: Perspectives in Ecological Complexity. University of Chicago Press (1982)
Holland, J.H.: Emergence: From chaos to order. Oxford University Press (2000)
Forrester, J.W.: Industrial dynamic. Journal of the Operational Research Society 48(10), 1037–1041 (1997)
Berrisford, G.: Discrete event modeling. In: OOIS, pp. 340–354. Springer, London (1997)
Janssen, M.A.: Agent-based modeling. In: Modeling in Ecological Economics, pp. 155–172 (2005)
Heath, S.K., Buss, A.: Cross-paradigm simulation modeling: challenges and successes. In: Proceedings of the Winter Simulation Conference, pp. 2788–2802 (2011)
Gilbert, N., Troitzsch, K.: Simulation for the social scientist. McGraw-Hill International (2005)
Siebers, P.-O., et al.: Discrete-event simulation is dead, long live agent-based simulation. Journal of Simulation 4(3), 204–210 (2010)
Sterman, J.D.: System dynamics: systems thinking and modeling for a complex world. In: Proceedings of the ESD Internal Symposium (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Wang, Y., Gu, J., Zhou, Z. (2014). Complex Adaptive Socio-Technical Systems Theory View of Ubiquitous Computing Systems Research. In: Hervás, R., Lee, S., Nugent, C., Bravo, J. (eds) Ubiquitous Computing and Ambient Intelligence. Personalisation and User Adapted Services. UCAmI 2014. Lecture Notes in Computer Science, vol 8867. Springer, Cham. https://doi.org/10.1007/978-3-319-13102-3_36
Download citation
DOI: https://doi.org/10.1007/978-3-319-13102-3_36
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13101-6
Online ISBN: 978-3-319-13102-3
eBook Packages: Computer ScienceComputer Science (R0)