Modular embedded system design for mechatronic education 2010 IEEE/ASME international conference on mechatronic and embedded systems and applications

Author(s):  
Ali Ozgu Nursal
Author(s):  
Xuan F. Zha ◽  
Ram D. Sriram

In this paper, we present our recent effort on using feature technology and ontology for embedded systems modeling and design. We present an overview of embedded system design and propose an object-oriented UML modeling approach to representing embedded systems, i.e., open embedded system model (OESM). OESM supports models of embedded system artifacts, components, features, configuration/assembly, and embedded system platform and family, design rationale, etc. Our focus is on modeling of feature semantic in embedded systems. We call this open embedded system feature model (OESFM). We also present a semantic web environment for modeling and verifying feature models using ontologies, in which the Prote´ge´-OWL is used to precisely capture the relationships among features in feature diagrams and configurations. The OESFM models and ontologies provide a feature-based component collaborative framework. This allows the designer to develop a virtual embedded system prototype through assembling virtual components in which the platform-based HW/SW co-design is supported and the design rationale is captured. The collaborative co-design framework can not only provide formal precise models of the embedded system prototypes but also offers design variation of prototypes whose members are derived by changing certain virtual components with different features.


2019 ◽  
Vol 4 (2) ◽  
pp. 40-44
Author(s):  
V. A. Kulkarni ◽  
G. R. Udupi

Embedded systems are portable battery powered devices that have limited power resource. Hence, most of embedded systems need to meet energy constraint. Performance and energy consumption are the most important metrics for embedded system design. Estimation of performance, energy utilization and its validation are essential for embedded system design. Attempt has been made to precisely measure software energy consumption by three methods on ARM Cortex M4 processor. The results are validated with five benchmark programs. Tedious calculation of inter instruction cost has been minimized by taking it as certain percent of total energy. Percentage error between actual and estimated energy is found to be less than 5%. 


Author(s):  
Umair Riaz ◽  
Sumair Aziz ◽  
Muhammad Umar Khan ◽  
Syed Azhar Ali Zaidi ◽  
Muhammad Ukasha ◽  
...  

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