approximation techniques for timing analysis of complex real-time embedded systems PDF
Preview approximation techniques for timing analysis of complex real-time embedded systems
Mälardalen University Press Licentiate Theses No. 122 Mälardalen University Press Licentiate Theses No. 122 APPROXIMATION TECHNIQUES FOR TIMING ANALYSIS OF COMPLEX REAL-TIME EMBEDDED SYSTEMS APPROXIMATION TECHNIQUES FOR TIMING ANALYSIS OF COMPLEX REAL-TIME EMBEDDED SYSTEMS Yue Lu 2010 Yue Lu 2010 School of Innovation, Design and Engineering School of Innovation, Design and Engineering Abstract Todate,manyindustrialembeddedsystemsareverylarge,flexible,andhighly configurable software systems, containing millions of lines of code and con- sisting of hundreds of tasks, many with real-time constraints, being triggered incomplex,nestedpatterns. Furthermore,thetemporaldependenciesbetween tasksinsuchsystemsaredifficulttodetermineanalytically,andtheyvarythe executiontimeandresponsetimeoftasksgreatly. Werefertosuchsystemsas ComplexReal-TimeEmbeddedSystems(CRTES). Tomaintain,analyzeandreusesuchCRTESisverydifficultandexpensive, which,nevertheless,offershighbusinessvalueinresponsetogreatconcernin industry. Moreover, in such context, not only the functional behavior of sys- temshastobeassured,butalsonon-functionalpropertiessuchasthetemporal behavior,i.e.,theWorst-CaseResponseTime(WCRT)oftheadheringtasksin systems has to be known. However, due to high complexity of such systems andthenatureoftheproblem, theexactWCRToftasksisimpossibletofind inpractice,butmayonlybebounded. Inaddition,theexistingrelativelywell- developedtheoriesformodelingandanalysisofreal-timesystemsarehaving problems, which limit their application in the context. In this thesis, we ad- dressthischallenge,andpresentaframeworkforapproximatetiminganalysis of CRTES that provides a tight interval of WCRT estimates of tasks by the usageofthreenovelcontributions. ThefirstcontributionisastatisticalapproachtoWCRTanalysisofCRTES. TheproposedalgorithmcombinesExtremeValueTheorywithotherstatistical Copyright © Yue Lu,2010 methods in order to produce a probabilistic WCRT estimate, using response ISBN 978-91-86135-83-6 timedatafromeitherMonteCarlosimulationsofadetailedmodelofthesys- ISSN 1651-9256 tem, or time-stamped traces of the real system execution. The focus of the Printed by Mälardalen University, Västerås, Sweden method is to give a WCRT prediction with a given probability of being ex- ceeded,whichpotentiallycouldbeconsideredasanupperboundontheWCRT estimate, especially in the case where conventional timing analysis methods i Abstract Todate,manyindustrialembeddedsystemsareverylarge,flexible,andhighly configurable software systems, containing millions of lines of code and con- sisting of hundreds of tasks, many with real-time constraints, being triggered incomplex,nestedpatterns. Furthermore,thetemporaldependenciesbetween tasksinsuchsystemsaredifficulttodetermineanalytically,andtheyvarythe executiontimeandresponsetimeoftasksgreatly. Werefertosuchsystemsas ComplexReal-TimeEmbeddedSystems(CRTES). Tomaintain,analyzeandreusesuchCRTESisverydifficultandexpensive, which,nevertheless,offershighbusinessvalueinresponsetogreatconcernin industry. Moreover, in such context, not only the functional behavior of sys- temshastobeassured,butalsonon-functionalpropertiessuchasthetemporal behavior,i.e.,theWorst-CaseResponseTime(WCRT)oftheadheringtasksin systems has to be known. However, due to high complexity of such systems andthenatureoftheproblem, theexactWCRToftasksisimpossibletofind inpractice,butmayonlybebounded. Inaddition,theexistingrelativelywell- developedtheoriesformodelingandanalysisofreal-timesystemsarehaving problems, which limit their application in the context. In this thesis, we ad- dressthischallenge,andpresentaframeworkforapproximatetiminganalysis of CRTES that provides a tight interval of WCRT estimates of tasks by the usageofthreenovelcontributions. ThefirstcontributionisastatisticalapproachtoWCRTanalysisofCRTES. TheproposedalgorithmcombinesExtremeValueTheorywithotherstatistical methods in order to produce a probabilistic WCRT estimate, using response timedatafromeitherMonteCarlosimulationsofadetailedmodelofthesys- tem, or time-stamped traces of the real system execution. The focus of the method is to give a WCRT prediction with a given probability of being ex- ceeded,whichpotentiallycouldbeconsideredasanupperboundontheWCRT estimate, especially in the case where conventional timing analysis methods i ii cannotbeapplied. Thesecondcontributionisaconcreteprocessofformallyobtainingtheex- actvalueofbothWorst-CaseExecutionTime(WCET)andWCRToftasksby usingupper-partbinarysearchalgorithmstogetherwithatimedmodelchecker, after a semantic-preserving model transformation. The underline premise is thatthesizeandcomplexityofCRTEShavetobereducedsuchthattheycan bemanageablebythemodelcheckingtool. Swedish Summary The third contribution is the application of an optimization algorithm, in this case a meta-heuristic search algorithm, on top of the traditional Monte Carlosimulation. Combiningoptimizationandsimulationhasshowntoyield substantially better results with respect to tight lower bounds on WCRT esti- matesoftasksinCRTES. Mångaavdagensindustriellainbyggdasystema¨rstoraochkomplicerade. De In addition, a number of tools have been implemented and used for the a¨r programvarusystem som innehåller miljontals rader programkod och de evaluation of the research results. These evaluations, using four simulation består av hundratals ko¨rbara programdelar (tasks). Programdelarna aktiveras modelsdepictingtwofictivebutrepresentativeindustrialcontrolapplications, ikomplicerademo¨nsterochdeharrealtidskrav–tidsma¨ssigtkorrektabeteen- give clear indication that the proposed methods have the potential to be both den och beroenden måste vara analyserbara, verifierbara och uppfyllda. Det applicableandusefulinpractice. a¨r mycket svårt att analysera alla realtidskrav eftersom exekveringstid och svårfo¨rutsa¨gbara exekveringsberoenden mellan tasks kan variera kraftigt. I dennaavhandlingkallarvidessaindustriellainbyggdakompliceradeprogram- varusystemenfo¨r(eng.)ComplexReal-TimeEmbeddedSystems,ellerCRTES. Deta¨rmycketsvårtattunderhålla,utvecklaochåteranva¨ndadessaCRTES idag, dådea¨rsåkomplicerade. Samtidigtsåkanindustrinintekastabortex- isterande CRTES och utveckla nya CRTES från bo¨rjan, då de representerar stora ekonomiska investeringar. Fo¨r att underla¨tta underhåll, utveckling och återanva¨ndningavindustriellainbyggdaprogramvarusystembeho¨verindustrin hja¨lp med nya metoder som kan sa¨kersta¨lla systemens funktionella och icke- funktionella beteenden. Exempel på icke-funktionella beteenden inkluderar dess tidsma¨ssiga beteenden. Den la¨ngsta mo¨jliga responstiden (eng. Worst- CaseResponseTime,ellerWCRT)avettprogramvausystemstasksmåstesa¨ker- sta¨llasanalytiskt,menpågrundsystemensho¨gakomplexitetkandetvaraomo¨j- ligt att hitta exakta WCRT uppgifter i praktiken; de kan bara uppskattas. Yt- terligare ett problem a¨r att de relativt va¨lutvecklade teorierna fo¨r analys och modelleringavrealtidssytema¨rvanligtvisfo¨rbegra¨nsadefo¨rattkunnatilla¨mp- aspåCRTES. Idennaavhandlingfo¨reslårviettramverkfo¨ranalysavCRTESsomha¨rled- erettintervallavWCRT-uppskattningarfo¨rtasks. Dettaramverkinnehållertre vetenskapligabidrag. Detfo¨rstabidrageta¨rennystatistiskmetodfo¨rWCRTanalysavCRTES. Denfo¨reslagnaalgoritmenkombinerarextremva¨rdesteorimedandrastatistiska iii ii cannotbeapplied. Thesecondcontributionisaconcreteprocessofformallyobtainingtheex- actvalueofbothWorst-CaseExecutionTime(WCET)andWCRToftasksby usingupper-partbinarysearchalgorithmstogetherwithatimedmodelchecker, after a semantic-preserving model transformation. The underline premise is thatthesizeandcomplexityofCRTEShavetobereducedsuchthattheycan bemanageablebythemodelcheckingtool. Swedish Summary The third contribution is the application of an optimization algorithm, in this case a meta-heuristic search algorithm, on top of the traditional Monte Carlosimulation. Combiningoptimizationandsimulationhasshowntoyield substantially better results with respect to tight lower bounds on WCRT esti- matesoftasksinCRTES. Mångaavdagensindustriellainbyggdasystema¨rstoraochkomplicerade. De In addition, a number of tools have been implemented and used for the a¨r programvarusystem som innehåller miljontals rader programkod och de evaluation of the research results. These evaluations, using four simulation består av hundratals ko¨rbara programdelar (tasks). Programdelarna aktiveras modelsdepictingtwofictivebutrepresentativeindustrialcontrolapplications, ikomplicerademo¨nsterochdeharrealtidskrav–tidsma¨ssigtkorrektabeteen- give clear indication that the proposed methods have the potential to be both den och beroenden måste vara analyserbara, verifierbara och uppfyllda. Det applicableandusefulinpractice. a¨r mycket svårt att analysera alla realtidskrav eftersom exekveringstid och svårfo¨rutsa¨gbara exekveringsberoenden mellan tasks kan variera kraftigt. I dennaavhandlingkallarvidessaindustriellainbyggdakompliceradeprogram- varusystemenfo¨r(eng.)ComplexReal-TimeEmbeddedSystems,ellerCRTES. Deta¨rmycketsvårtattunderhålla,utvecklaochåteranva¨ndadessaCRTES idag, dådea¨rsåkomplicerade. Samtidigtsåkanindustrinintekastabortex- isterande CRTES och utveckla nya CRTES från bo¨rjan, då de representerar stora ekonomiska investeringar. Fo¨r att underla¨tta underhåll, utveckling och återanva¨ndningavindustriellainbyggdaprogramvarusystembeho¨verindustrin hja¨lp med nya metoder som kan sa¨kersta¨lla systemens funktionella och icke- funktionella beteenden. Exempel på icke-funktionella beteenden inkluderar dess tidsma¨ssiga beteenden. Den la¨ngsta mo¨jliga responstiden (eng. Worst- CaseResponseTime,ellerWCRT)avettprogramvausystemstasksmåstesa¨ker- sta¨llasanalytiskt,menpågrundsystemensho¨gakomplexitetkandetvaraomo¨j- ligt att hitta exakta WCRT uppgifter i praktiken; de kan bara uppskattas. Yt- terligare ett problem a¨r att de relativt va¨lutvecklade teorierna fo¨r analys och modelleringavrealtidssytema¨rvanligtvisfo¨rbegra¨nsadefo¨rattkunnatilla¨mp- aspåCRTES. Idennaavhandlingfo¨reslårviettramverkfo¨ranalysavCRTESsomha¨rled- erettintervallavWCRT-uppskattningarfo¨rtasks. Dettaramverkinnehållertre vetenskapligabidrag. Detfo¨rstabidrageta¨rennystatistiskmetodfo¨rWCRTanalysavCRTES. Denfo¨reslagnaalgoritmenkombinerarextremva¨rdesteorimedandrastatistiska iii iv metoderfo¨rattlevereraenWCRTfo¨rtasks. MetodengerenWCRTuppskat- tningsomkanbetraktassomeno¨vregra¨nsavWCRTfo¨rsystemda¨rkonven- tionellrealtidsanalysintekantilla¨mpas. Det andra bidraget a¨r en konkret process fo¨r att erhålla exakta va¨rden av va¨rstamo¨jligaexekveringstider(eng. Worst-CaseExecutionTime,ellerWCE- T)ochWCRTavtasksgenomatttilla¨mpaso¨kalgoritmerochformellametoder. Det tredje bidraget a¨r kombinationen av optimeringsalgoritmer och tradi- tionellMonteCarlo-simuleringvilketvisarsiggebraresultatfo¨rla¨gregra¨nser påWCRTavtasksiCRTES. One day, you might look up and see me playing the Alla bidrag har utva¨rderats på modeller av komplexa inbyggda program- gameat50. Don’tlaugh. Neversayneverbecauselim- varusystemochresultatengerentydligindikationpåattdefo¨reslagnametoder- naa¨rpraktisktanva¨ndbara. its,likefears,areoftenjustanillusion. –MichaelJordan AFormerAmericanProfessionalBasketballPlayerandActiveBusinessman AtNaismithMemorialBasketballHallofFame2009 iv metoderfo¨rattlevereraenWCRTfo¨rtasks. MetodengerenWCRTuppskat- tningsomkanbetraktassomeno¨vregra¨nsavWCRTfo¨rsystemda¨rkonven- tionellrealtidsanalysintekantilla¨mpas. Det andra bidraget a¨r en konkret process fo¨r att erhålla exakta va¨rden av va¨rstamo¨jligaexekveringstider(eng. Worst-CaseExecutionTime,ellerWCE- T)ochWCRTavtasksgenomatttilla¨mpaso¨kalgoritmerochformellametoder. Det tredje bidraget a¨r kombinationen av optimeringsalgoritmer och tradi- tionellMonteCarlo-simuleringvilketvisarsiggebraresultatfo¨rla¨gregra¨nser påWCRTavtasksiCRTES. One day, you might look up and see me playing the Alla bidrag har utva¨rderats på modeller av komplexa inbyggda program- gameat50. Don’tlaugh. Neversayneverbecauselim- varusystemochresultatengerentydligindikationpåattdefo¨reslagnametoder- naa¨rpraktisktanva¨ndbara. its,likefears,areoftenjustanillusion. –MichaelJordan AFormerAmericanProfessionalBasketballPlayerandActiveBusinessman AtNaismithMemorialBasketballHallofFame2009 To the Maomao World Where there are only Maomaos, Xiao gougou, and the Chocolate Factory. To the Maomao World Where there are only Maomaos, Xiao gougou, and the Chocolate Factory. Preface and Acknowledgments Now, we are going in the thanksgiving chapter, which is the hardest part for metowrite,eventostart,butmightbethemostinterestingchapter(outofall thechaptersinthiswholethesis)foryoutoread. Soletusdroptheless“tasty” maincourseofthethesisfornow,beltupandstartthisthanksgivingjourney! ThejourneystartedonalovelysummerdayinSønderborg,Denmark,back in the year 2005. I was graduated from the University of Southern Denmark by ending with a Master’s degree in Mechatronics, and I made up my mind to further my study to become a doctor1. After sending out countless num- ber of application emails to different universities, I was luckily enough to be accepted by Ma¨lardalen Real-Time Research Centre (MRTC) in Ma¨lardalen University. Honestlyspeaking, Iwasreallyexpectingthisunexpected. Since I never, ever thought about starting my new dating with a caring, beautiful and elegant blonde! Thank you Hans Hansson, Christer Norstro¨m and Bjo¨rn Lisper,forgivingmethisopportunity! Tome,thisthesisisneithertheendofthebeginningofthejourney,northe beginningoftheendofthejourney. Instead,ittakesmesomewhereoutthere. Along with this rewarding journey, I have my pleasure to enjoy the scenery andexperiencelife. Throughoutthesepastyears,Imetdifferentpeoplearound the world, with whom I had lots of fun, from whom I knew more about my weaknesses,andwhomIwouldlovetoparrot. Inthefollowingcontext,Iwill categorizethosepeople,whohaveplayeddifferentrolesinmyshortlife. Supervisors Withoutyoursencouragement,guidanceandpatience,Iwould nevereverproceededtotheplacewhereIamnow. 1Thedoctorbutnotthekindthathelpspeople. ix
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