By Twan Basten, Roelof Hamberg, Frans Reckers, Jacques Verriet
ISBN-10: 1461448204
ISBN-13: 9781461448204
This ebook describes model-based improvement of adaptive embedded platforms, which allow superior performance utilizing a similar assets. The options offered facilitate layout from a better point of abstraction, targeting the matter area instead of at the answer area, thereby expanding improvement potency. types are used to trap procedure requirements and to enforce (manually or immediately) process performance. The authors exhibit the genuine influence of adaptivity on engineering of embedded structures via supplying numerous commercial examples of the types utilized in the improvement of adaptive embedded platforms.
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Additional info for Model-Based Design of Adaptive Embedded Systems
Example text
Thesis, University of Twente, Enschede (2012) 7. : Experiences and lessons learned using UML-RT to develop embedded printer software. , Komi-Sirvi¨o, S. ) Product Focused Software Process Improvement. Lecture Notes in Computer Science, vol. 2559, pp. 475–484. Springer, Berlin (2002) 8. : Essentials of Project and Systems Engineering Management. Wiley, Hoboken (2008) 9. : Survey of model-based systems engineering (MBSE) methodologies. Technical Report INCOSE-TD-2007-003-01, INCOSE, San Diego (2008) 10.
This leads to more involved situations, sketched in Fig. 8, in which the values for 2 Aspects of Adaptive Systems Engineering: A Professional Printing Case 23 Fig. 8 A schematic representation of the working range and two possible practical working ranges for two independent control parameters. Note that the two working ranges reflect different trade-offs, while they are both within the available working range. The bold line indicates the set of optimal working points (cf. Fig. 9). Different context conditions will lead to different curves and working ranges independent control parameters influence each other through the need for sufficient quality.
A model is a simplified representation of the system itself, mostly focused on a few aspects of that system. A model that is able to reconstruct (an approximation of) the operational behaviour of a system is often called an executable model (see executable architectures, executable UML [9]). These models play an important role in designing adaptive systems, because in order to design correct and understandable system behaviour it is necessary to reason about dynamic properties of the system. Measurements on prototype systems can either be summarised by relatively simple relationships in such models, or point out problem areas where insights are lacking.