Fault tolerant embedded systems design by multi-objective optimization

被引:12
作者
Martinez-Alvarez, Antonio [1 ]
Restrepo-Calle, Felipe [1 ]
Vivas Tejuelo, Luis Alberto [1 ]
Cuenca-Asensi, Sergio [1 ]
机构
[1] Univ Alicante, Comp Technol Dept, Alicante 03690, Spain
关键词
Multi-objective optimization; NSGA-II; Embedded systems design; Soft error; Fault tolerance; ERROR-DETECTION; EVOLUTIONARY ALGORITHMS; MITIGATION;
D O I
10.1016/j.eswa.2013.06.060
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The design of fault tolerant systems is gaining importance in large domains of embedded applications where design constrains are as important as reliability. New software techniques, based on selective application of redundancy, have shown remarkable fault coverage with reduced costs and overheads. However, the large number of different solutions provided by these techniques, and the costly process to assess their reliability, make the design space exploration a very difficult and time-consuming task. This paper proposes the integration of a multi-objective optimization tool with a software hardening environment to perform an automatic design space exploration in the search for the best trade-offs between reliability, cost, and performance. The first tool is commanded by a genetic algorithm which can simultaneously fulfill many design goals thanks to the use of the NSGA-II multi-objective algorithm. The second is a compiler-based infrastructure that automatically produces selective protected (hardened) versions of the software and generates accurate overhead reports and fault coverage estimations. The advantages of our proposal are illustrated by means of a complex and detailed case study involving a typical embedded application, the AES (Advanced Encryption Standard). (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:6813 / 6822
页数:10
相关论文
共 36 条
[1]  
[Anonymous], 2001, P 5 C EVOLUTIONARY M
[2]  
[Anonymous], 1994, EVOL COMPUT
[3]  
[Anonymous], 2001, P 6 INT C PAR PROBL
[4]   Performance evaluation of efficient multi-objective evolutionary algorithms for design space exploration of embedded computer systems [J].
Ascia, Giuseppe ;
Catania, Vincenzo ;
Di Nuovo, Alessandro G. ;
Palesi, Maurizio ;
Patti, Davide .
APPLIED SOFT COMPUTING, 2011, 11 (01) :382-398
[5]  
Baumann R., 2002, IEEE 2002 RELIABILIT, P121
[6]   Radiation-induced soft errors in advanced semiconductor technologies [J].
Baumann, RC .
IEEE TRANSACTIONS ON DEVICE AND MATERIALS RELIABILITY, 2005, 5 (03) :305-316
[7]  
Corne D. W., 2000, Parallel Problem Solving from Nature PPSN VI. 6th International Conference. Proceedings (Lecture Notes in Computer Science Vol.1917), P839
[8]   A Novel Co-Design Approach for Soft Errors Mitigation in Embedded Systems [J].
Cuenca-Asensi, Sergio ;
Martinez-Alvarez, Antonio ;
Restrepo-Calle, Felipe ;
Palomo, Francisco R. ;
Guzman-Miranda, Hipolito ;
Aguirre, Miguel A. .
IEEE TRANSACTIONS ON NUCLEAR SCIENCE, 2011, 58 (03) :1059-1065
[9]   A fast and elitist multiobjective genetic algorithm: NSGA-II [J].
Deb, K ;
Pratap, A ;
Agarwal, S ;
Meyarivan, T .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (02) :182-197
[10]   Technical standard for atmospheric radiation single event effects, (SEE) on avionics electronics [J].
Edwards, R ;
Dyer, C ;
Normand, E .
2004 IEEE RADIATION EFFECTS DATA WORKSHOP, WORKSHOP RECORD, 2004, :1-5