Context-Aware Model for Dynamic Adaptability of Software for Embedded Systems

Authors

  • Camille Jaggernauth Simon Fraser University
  • Bozena Kaminska
  • Douglas Gubbe

Keywords:

fuzzy cognitive maps, embedded software architecture, adaptability, context-aware model, wireless sensor networks.

Abstract

Context-awareness is an important topic in the wireless sensor networks research field. Wireless sensor networks comprise wirelessly enabled embedded systems for data acquisition and control for a wide array of applications. This paper introduces a novel embedded systems firmware model based on a layered model with context and cognitive planes. The novel architecture focuses on dynamic adaptability. The context plane features a micro-architecture which includes context collectors, context controllers and a context task based coordinator. The cognitive plane is responsible for dynamic adaptable logic reconfiguration inspired by fuzzy cognitive maps. No previous work has been done on the use of fuzzy cognitive maps for enabling dynamic, resource constrained, and firmware adaptability. An industrial application (Novax’s Accessible Pedestrian System) and simulations using the Rapita suite of tools are presented for model proof of concept and evaluation.

 

Author Biography

Camille Jaggernauth, Simon Fraser University

Camille Jaggernauth BASc '98, MEng '08 is a PhD candidate at Simon Fraser University. Camille has worked in industry for over 13 years as a firmware engineer. Her research interests are firmware, embedded systems and wireless sensor networks.

References

C. Jaggernauth, B. Hung, P. Lin, Y. Chuo, B. Kaminska, “Test Firmware Architecture for a Flexible Wireless Physiological Multi-Sensor.” IEEE International Conference on Man, Systems and Cybernetics, Oct. 2011.

C. Jaggernauth, B. Hung, P. Lin, Y. Chuo, B. Kaminska, “Optimized, Practical Firmware Design For a Novel Flexible Wireless Multi-Sensor Platform for Body Activity And Vitals Monitoring.” IEEE International Conference on Consumer Electronics, pp 551-552, Jan. 2011.

K.B.R.G.T. Samarasinghe, M.M.N.N. Jayasekara, D. Elkaduwe and R.G. Ragel, “Power Aware Instruction Scheduling for Microcontrollers,” International Journal of Scientific and Research Publications, vol. 2(10), October 2012.

Armoush Ashraf. “Design Patterns for Safety-Critical Embedded Systems.” Ph.D. thesis, RWTH AAChen, Germany, 2010.

A.K. Dey, G.D. Abowd and D. Salber, “A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications.” Hum.-Comput. Interact, vol. 16-2, pp 97-166, 2001.

N. Medvidovic, “Software Architectures and Embedded Sytems: A Match Made in Heaven.” IEEE Software, September/October 2005.

P. Inverardi and M. Tivoli, “The Future of Software: Adaptation and Dependability.” ISSSE 2006-2008, LNCS 5413, Springer-Verlag Berlin, Heidelberg, pp 1-31, 2009.

N. Gamez et al., “Context-Awareness in Wireless Sensor Networks: A Middleware Solution.” Sensors, 2012.

C. Jaggernauth, “Modeling Returned Biomedical Devices in a Lean Manufacturing Environment,” in Computational Models of Complex Systems, Intelligent Systems Reference Library, Springer, 2014, Chapter 8.

G. Buyukozkan and Z. Vardaloglu, “Analyzing of collaborative planning, forecasting and replenishment approach using fuzzy cognitive map.” International Conference on Computers and Industrial Engineering, 2009.

F. Mastrogiovanni, A. Scalmato, A. Sgorbissa, “Affordance-Based Planning for Assisting Humans in Daily Activities.” Sixth International Conference on Intelligent Environments (IE), 2010.

D.K. Iakovidis and E. Papageorgiou, “Intuitionistic Fuzzy Cognitive Maps for Medical Decision Making.” IEEE Transactions on Information Technology in Biomedicine, Jan 2011.

E.I. Papageorgiou, N.I. Papandrianos and D. Apostolopoulos, P. Vassilakos, “Complementary use of Fuzzy Decision Trees and Augmented Fuzzy Cognitive Maps for Decision Making in Medical Informatics.” International Conference on BioMedical Engineering and Informatics, BMEI 2008.

E. Papageorgiou et al., “A Fuzzy Cognitive Map based tool for prediction of infectious diseases.” FUZZ-IEEE, 2009.

G. Krasner and S. Pope, “A Cookbook for Using the Model-View-Controller User Interface Paradigm in Smalltalk -80.” Journal of Object Oriented Programming (JOOP), August/September 1988.

S. Pantsar-Syvaniemi, “Architecting Embedded Software for Context-Aware Systems,” in Embedded Systems - Theory and Design Methodology, InTech, 2012.

D.L. Parnas, “On the criteria to be used in decomposing systems into modules.” Commun. ACM, vol. 15(12), pp 1053-1058, 1972.

D.L. Parnas “Designing software for Ease of Extension and Contraction.” IEEE Trans. Software Eng, vol. 5(2), pp 128-138, 1979.

D. Kardaras and B. Karakostas, “The use of fuzzy cognitive maps to simulate the information systems strategic planning process.” Information and Software Technology, 1999.

M. Hamilton, “Software Development: A Guide to Building Reliable Systems.” Prentice Hall, 1999.

T. McCabe, “A Complexity Measure.” IEEE Transactions on Software Engineering, vol. 2, no. 4, 1976.

Rapita. RapiTime. Internet: http://www.rapitasystems.com/products/RapiTime, [May 20, 2015].

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Published

2015-11-08

How to Cite

Jaggernauth, C., Kaminska, B., & Gubbe, D. (2015). Context-Aware Model for Dynamic Adaptability of Software for Embedded Systems. International Journal of Computer (IJC), 19(1), 91–113. Retrieved from https://ijcjournal.org/index.php/InternationalJournalOfComputer/article/view/491

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Articles