Self-Aware Computing: A Primer

Matthew N. O. Sadiku, Mahamadou Tembely, Sarhan M. Musa


The term self-awareness has been adopted from biology and cognitive science. It refers to the capability of a system to obtain and react upon certain knowledge. It has been proposed as a means for advance autonomous adaptive behavior for complex systems. Self-aware computing is a paradigm for structuring and simplifying the design and operation of complex, dynamic computing systems.  This paper provides a brief introduction to self-aware computing.

Full Text:



N . Gill, “Comparison of self-aware and organic computing systems,”

A. Agne et al., “Self-awareness as a model for designing and operating heterogeneous multicores,” ACM Transactions on Reconfigurable Technology and Systems, vol. 7, no. 2, June 2014.

T. Chen et al., The Handbook of Engineering Self-Aware and Self-Expressive Systems, 2014,

P. R. Lewis, “Architectural aspects of self-aware and self expressive computing systems: From psychology to engineering,” Computer, vol. 48, no. 8, August 2015, pp. 62-70.

P. R. Lewis, “Self-aware computing systems: From psychology to engineering,” Design, Automation and Test in Europe, 2017, pp. 1044-1049.

H. Hoffmann and M. Maggio, “SEEC: A framework for self-aware computing,”


L. D. Paulson, “DARPA creating self-aware computing,” Computer, vol. 36, no. 3, March 2003, p. 24.

H. Hoffmann et al., “SEEC: A general and extensible framework for self-aware computing,” 2011,

S. Kounev et al. (eds.), “Model-driven algorithms and architectures for self-aware computing systems,” January 2015,

P. R. Lewis et al. (eds.), Self-aware Computing Systems: An Engineering Approach. Springer, 2016.

S. Kounevet al. (eds.), Self-aware Computing Systems. Springer, 2017.



  • There are currently no refbacks.

© International Journals of Advanced Research in Computer Science and Software Engineering (IJARCSSE)| All Rights Reserved | Powered by Advance Academic Publisher.