Guiding Genetic Algorithms using importance measures for reliable design of embedded systems

2016 ◽  
Author(s):  
Hananeh Aliee ◽  
Stefan Vitzethum ◽  
Michael Glass ◽  
Jurgen Teich ◽  
Emanuele Borgonovo
Keyword(s):  
Genetic Algorithms ◽  
Embedded Systems ◽  
Reliable Design

Genetic Algorithms

2014 ◽  
pp. 239-255 ◽  
Author(s):  
Pabitra Mohan Khilar
Keyword(s):  
Genetic Algorithms ◽  
Fault Diagnosis ◽  
Distributed Computing ◽  
Embedded Systems ◽  
Distributed Embedded Systems ◽  
Distributed Computing Systems ◽  
Computing Systems ◽  
Satellite Systems ◽  
Complete Problems ◽  
Diagnosis Algorithm

Genetic Algorithms are important techniques to solve many NP-Complete problems related to distributed computing and its application domains. Genetic algorithm-based fault diagnoses in distributed computing systems have been a feasible methodology to solve diagnosis problems recently. Distributed embedded systems consisting of sensors, actuators, processors/microcontrollers, and interconnection networks are one class of distributed computing systems that have long been used, staring from small-scale home appliances to large-scale satellite systems. Some of their applications are in safety-critical systems where occurrence of faults can result in catastrophic situations for which fault diagnosis in such systems are very important. In this chapter, different types of faults, which are likely to occur in distributed embedded systems and a GA-based methodology to solve these problems along with the performance analysis of fault diagnosis algorithm have been presented. Nevertheless, the diagnosis algorithm presented here is well suitable for general purpose distributed computing systems with appropriate modification over system and fault model. In fact, this book chapter will enable the reader not only to study various aspects of fault diagnosis techniques but will also provide insight to build robust systems to allow for continued normal service despite the occurrence of failures.

scholarly journals Optimization methodology of dynamic data structures based on genetic algorithms for multimedia embedded systems

2009 ◽  
Vol 82 (4) ◽  
pp. 590-602 ◽  
Author(s):  
Christos Baloukas ◽  
Jose L. Risco-Martin ◽  
David Atienza ◽  
Christophe Poucet ◽  
Lazaros Papadopoulos ◽  
...  
Keyword(s):  
Genetic Algorithms ◽  
Embedded Systems ◽  
Data Structures ◽  
Dynamic Data Structures ◽  
Dynamic Data ◽  
Optimization Methodology

Multi-objective optimization of multimedia embedded systems using genetic algorithms and stochastic simulation

2016 ◽  
Vol 21 (14) ◽  
pp. 4141-4158 ◽  
Author(s):  
Bruno Nogueira ◽  
Paulo Maciel ◽  
Eduardo Tavares ◽  
Ricardo M. A. Silva ◽  
Ermeson Andrade
Keyword(s):  
Genetic Algorithms ◽  
Embedded Systems ◽  
Stochastic Simulation ◽  
Multi Objective Optimization ◽  
Multi Objective

A hybrid approach to testing for nonfunctional faults in embedded systems using genetic algorithms

2018 ◽  
Vol 28 (7) ◽  
pp. e1686 ◽  
Author(s):  
Tingting Yu ◽  
Witawas Srisa-an ◽  
Myra B. Cohen ◽  
Gregg Rothermel
Keyword(s):  
Genetic Algorithms ◽  
Embedded Systems ◽  
Hybrid Approach

Genetic Algorithms—a Tool for OR?

1996 ◽  
Vol 47 (4) ◽  
pp. 550-561 ◽  
Author(s):  
Kathryn A Dowsland
Keyword(s):  
Genetic Algorithms
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