Contributions to the Design of Reconfigurable Embedded Systems: from Modelling to Implementation Jean-Christophe Prévotet

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Jean-Christophe Prévotet. Contributions to the Design of Reconfigurable Embedded Systems: from Modelling to Implementation. Hardware Architecture [cs.AR]. Université de Rennes1, 2019. ￿tel- 02415974￿

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Contributions to the Design of Reconfigurable Embedded Systems: from Modelling to Implementation

Jean-Christophe Prévotet

Maître de Conférences à l’INSA de Rennes Laboratoire IETR / Équipe de recherche SYSCOM

A soutenir le 07/06/2019 devant le jury composé de

Rapporteurs Diana Göhringer Professeure au TU, Dresden Christophe Jégo Professeur à ENSEIRB-MATMECA, IMS, Bordeaux Gilles Sassatelli Directeur de recherche CNRS, LIRMM, Montpellier Examinateurs Guy Gogniat Professeur à l’université de Bretagne-Sud, Lab-STICC Christophe Moy Professeur à l’université de Rennes 1, IETR Frédéric Pétrot Professeur à l’université de Grenoble, TIMA Fabienne Nouvel Maître de conférences HDR, INSA de Rennes, IETR

Sommaire

Part. II 1 Synthesis of Research Works ...... 1 Preliminaries...... 3 111 Introduction ...... 4 Chap. 1 Summary of studies ...... 4 1.1 OS Modelling ...... 4 1.2 Reconfiguration Management ...... 5 1.3 Power Modelling ...... 6 2 Historical Research Background ...... 7 2.1 PhD Studies ...... 7 2.2 ETIS 2002-2007 ...... 7 2.3 IETR 2007- Today ...... 7 222 From OS Modelling to Implementation ...... 9 Chap. 1 Context and Related Works ...... 9 2 A new Design Methodology for Operating Systems ...... 11 2.1 System Specifications ...... 12 2.2 The Dogme Tool ...... 14 3 OS Model Description ...... 14 3.1 Task Manager Service ...... 15 3.2 Scheduling Service ...... 16 3.3 The IRQ Manager Service ...... 16 3.4 The Communication Service ...... 16 3.5 The Intercommunication Service ...... 16 3.6 The Reconfiguration Management Model ...... 17 3.6.1 The HW Task Concept ...... 18 3.6.2 The Dispatcher ...... 18 3.6.3 The placer ...... 19 3.6.4 The Offloader ...... 19 4 Modelling Evaluation ...... 20 4.1 Description ...... 21 4.2 System Model ...... 22 4.2.1 Application Model ...... 22 4.2.2 Architecture Model ...... 23 4.2.3 Kernel Model ...... 23 4.3 Simulation and results ...... 24 5 OS Code Generation ...... 25 5.1 OS Meta-model ...... 26 5.2 Model to Model Transformation ...... 27 6 From the OS to the Hypervisor ...... 27 6.1 Is virtualization compatible with real time constraints ? ...... 27 6.2 Virtualization Overhead ...... 29 6.3 Overhead aware schedulability analysis ...... 30 6.4 Proposal : Ker-ONE : A lighweight Micro-Hypervisor ...... 33 iii Sommaire

6.4.1 Overview ...... 33 6.4.2 Resource Virtualization ...... 34 6.4.3 Event Management ...... 35 6.5 Performance Evaluation ...... 35 6.5.1 Basic Virtualization Functions Overhead ...... 35 6.5.2 RTOS Virtualization Evaluation ...... 38 7 Summary ...... 39 333 Reconfiguration Management ...... 40 Chap. 1 Context and Related Works ...... 40 2 General Framework ...... 45 3 HW Level ...... 45 3.1 HW Task Model ...... 45 3.2 PRR HW Management ...... 47 3.3 The PRR Monitor ...... 48 4 OS Level ...... 48 4.1 The Configuration Controller (Virtual Device Manager) ...... 48 4.2 Other OS services to handle reconfiguration ...... 49 4.2.1 The Parameters Provider ...... 50 4.2.2 The HW Updater ...... 50 4.3 The particular case of Virtualization : Security Mechanisms ...... 50 5 Application level ...... 51 5.1 Context ...... 51 5.2 Case study : VHA for WI-FI and WiMax heterogeneous networks ...... 52 5.3 The Adaptive Scoring System ...... 52 5.4 Towards a Smart Reconfiguration Management ...... 54 5.4.1 Overview ...... 54 5.4.2 Modules Description ...... 54 5.5 Results ...... 56 6 Performances Evaluation ...... 57 6.1 Overhead Analysis ...... 59 6.2 Experiments and Results ...... 60 6.2.1 Description ...... 60 6.2.2 Results ...... 61 7 Summary ...... 62 444 From Power Modeling to highly Energy-Efficient Devices ...... 64 Chap. 1 Context and Related Works ...... 64 2 The Classic Implementation Approach ...... 67 2.1 Studying New Waveforms ...... 68 2.2 Proposed Offline Hardware Platform ...... 69 2.2.1 System Description ...... 69 2.2.2 Studied configurations ...... 70 2.2.3 Results ...... 71 2.3 Studying the SW limitations ...... 73 2.4 The Receive Spatial Modulation scheme ...... 77 2.4.1 Prototype Description ...... 77 2.4.2 Results ...... 78 3 Evaluation of FPGA-Based Wireless Communications Systems ...... 79 3.1 Proposed approach ...... 80 3.1.1 Scenario Definition ...... 80 3.1.2 IP Characterization ...... 81 3.1.3 Modeling and High Level Simulation ...... 82 iv Sommaire

3.2 Use Case ...... 84 3.2.1 System Description ...... 84 3.2.2 Power Estimation ...... 85 3.2.3 Power Estimation Speed-Up ...... 86 4 Towards Fine grain Modeling ...... 86 4.1 Analytical Modeling ...... 86 4.2 Extension to other FPGA Devices ...... 87 4.3 Neural Networks based Modeling ...... 87 4.3.1 Model Definition ...... 89 4.3.2 Results ...... 90 5 Summary ...... 92 555 Research Perspectives ...... 93 Chap. 1 Embedded Systems Virtualization ...... 93 1.1 Hypervisor structure ...... 93 1.2 Reconfigurable Hardware Resources Sharing ...... 94 1.3 VM Scheduling and Off-Loading Service ...... 94 2 End to End Reconfiguration Management ...... 94 2.1 Multi-standards Reconfiguration ...... 95 2.2 Machine Learning ...... 95 3 Towards Energy-Efficient Communicating Devices ...... 96 3.1 New Waveforms ...... 96 3.2 Hardware Power Models ...... 96 3.3 From Device to Protocol ...... 97 Bibliography...... 99

v Sommaire

vi Partie I

Synthesis of Research Works

1

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PARCOURS PROFESSIONNEL SYNTHESISOF RESEARCH WORKS APPENDIX h sensor The PARCOURS other P In ROFESSIONNEL changes. signals. configuration received the despite the operation decode the continuously interrupt to not able should system is the it words, if paths. guaranteed multiple is e.g. two system channel, of the 10 transmission of last effects the pause side between to this due S in case, is and our This YNTHESISOF frame In required. a is pause to a equivalent frames, is signal each Moreover, RESEARCH WORKS APPENDIX SYSTEM TARGET THE OF DESCRIPTION 6.1. h eaiu ftercie srpeetdi iue63 h orcns fthe of correctness The 6.3. Figure in represented is receiver the of behaviour The iue62 pcrlecec safnto fteSRwt C.Suc [80] Source ACM. with SNR the of function a as efficiency Spectral 6.2: Figure h N.Weee h hne odtoschange, conditions channel the Whenever SNR. the .Nt htteClmsadRw fteMStasks MCS the of Rows and Columns the time. that processing Note frame from [CCLJ12 the ]. extracted FPGA been to have Virtex5 respect sizes bitstream’s a with their as negligible on well as is implementation times task an a execution their this Assuming tasks, systems. of MCS communication the time Regarding of the implementations estimation, previous channel of basic results the to according estimated The The sensor The e side to due 10 is lasts This pause duration. this frames. case, two our of In transmission paths. multiple the between required is pause 4.2.1 Table : following the are system the constitute that tasks The MCS MCS iso.Weee hneo h hne’ odtosi eetd hsts eoe h current the becomes task this detected, is conditions channel’s the MCS. on change a Whenever mission. fec rm,tets ssseddfrteitrfaetm.Atrtepue MCS by pause, indicated the itself. been deletes After has time. change inter-frame channel a the time for by suspended required is is that task MUTEX the frame, each of Afterwards, transmission. change, conditions channel the ver 4.2 F n c IGURE ts a been has task sensor the of time execution The task. system each of attributes the lists 2.7 aki epnil o npcigtetasiso hne n estimating and channel transmission the inspecting for responsible is task plcto Model Application akrpeet h C ceeta sbigue o h urn rnmsin tteend the At transmission. current the for used being is that scheme MCS the represents task akrpeet h C ceeta a encngrdb the by configured been has that scheme MCS the represents task aki epnil o npcigtetasiso hne n siaigteSR Whene- SNR. the estimating and channel transmission the inspecting for responsible is task ytmModel System iue63 tt ahn ftecs td scenario. study case the of machine State 6.3: Figure Seta e Spectral – 2.9 sensor ffi sensor inya ucino h N ihAM ore[CCEPO12 ] Source ACM. with SNR the of function a as ciency µ ,wihi prxmtl 0 ftefaesduration. frame’s the of 10% approximately is which s, ok naMTXutltenx rnmsini started. is transmission next the until MUTEX a on locks oidct htanwtasiso sgigt esatd Every started. be to going is transmission new a that indicate to , sensor hpte2 rmO oeln oImplementation to Modelling OS From 2. Chapitre µ s ofiue h C hti h otsial o h next the for suitable most the is that MCS the configures hc orsod prxmtl o1%o h frame’s the of 10% to approximately corresponds which , 22 sensor the , MCS c ciae h etMSshm and scheme MCS next the activates sensor

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Figure in illustrated as meta-model, RTOS structural the of instance model Af meta-model. a RTOS structural by the used in present entity ”Service” the and model conforms to model- a called is discipline. technique engineering This model-driven the in model. transformation RTOS structural a into model simulation SoC oceey ecet apn ewe h Cmoet niypeeti th in present entity ”Component” the between mapping a create we Concretely, hspoescudb uoaial ple naysmlto oe ntneo th of instance model simulation any on applied automatically be could process This hstcnqerle ntefc htaymt-oe smnaoydfie us defined mandatory is meta-model any that fact the on relies technique This OveRSoC RTOSOveRSoC model n aheeetfo a from element each and meta-model RTOS OveRSoC F rnfrainengine transformation IGURE oatmtclypouetefia xctbeprograms. executable final the produce automatically to A conforms to n aheeetfo meta-model a from element each and Mdlt oe rnfrainprocess. transformation model to Model – 2.14 iue51:Mdlt-oe rnfrainprocess. transformation Model-to-Model 5.11: Figure µ ocnetamdlisac fteOeSCmt-oe noa into meta-model OveRSoC the of instance model a convert to O-I.Ti oicto sncsaybcuetefia source final the because necessary is modification This cOS-II). eamdlB meta-model M Transformation Engine ta transformation conforms to Object FacilityObject mapping mapping ffi 27 122 inyo ita ytm ntrso efrac and performance of terms in systems virtual of ciency rnfrainengine transformation sln sbt eamdl r endusing defined are meta-models both as long as Figure RTOS structuremodel conforms to ffi meta-model RTOS structure 2.14. in ntecs hr hr sonly is there where case the in cient rdc sa upta output an as produce , B sln sbt eamdl are meta-models both as long as e ht hsrl is rule this that, ter vro meta- OverSoC e n h MetaOb- the ing tfo a from nt h developed the e recd of code urce OveRSoC e to-model meta-

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average release-delay in milleseconds average release-delay in milleseconds 1000 1500 2000 2500 1000 1500 2000 2500 500 500 0 0 . 1 1 deadline task4:2400.0ms faproi ak hc stedifference the is which task, periodic a of VM 2 2 2 . VM(160ms,200ms),task3(300ms,1200ms)&task4(400ms,2400ms) Task set2executedonaLinux-PREEMPT_RTusingonekvmVM VM(160ms,200ms),task1(30ms,150ms)&task2(50ms,200ms) 3 3 Task set1testedonaLinux-PREEMPT_RTusingkvmVM d ees delay Release (d) delay Release (b) 4 4 oosretebehavior the observe to r Number ofruns Number ofruns 5 5 DMR w eaaevirtual separate two n ns ie hnwe Then time. finish n ediems in miss deadline any iue41() Fig- 4.12(a), Figure 6 6 erct verify to metric o’ release job’s y 7 7 ia”release tical” task 3[dmr10.0%] task 4[dmr0.0%] task 2[dmr0.0%] task 1[dmr0.0%] deadline task3:1200.0ms deadline task1:1500.0ms deadline task2:2000.0ms ’s 8 8 verhead. release 9 9 10 10

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Chapitre ehiuscnit nmxmzn h hne aaiywiemnmzn h po- adaptive the the minimizing of while goals capacity main channel the the of One maximizing time. in real consists in techniques adapt environment appropriately the and and to decide QoS, system to the allocation, investigated been guarantee resource also to have as used consumption, such power been parameters, have Va- high-level (BER) system. (RSSI), Rate Other wireless Indicator Error adaptability. Strength the Bit Signal (SNR), of Received Ratio part the Signal-to-Noise as recongure such to systems parameters Such low-level decide rious properties. and channel analyze, to learn, according waveforms sense, adapt to systems reless ecient and fast apply to how or Also, made ? state be channel can wireless that new ? decision reconguration the optimal detect parame- the to what Each is analyzed example not. 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PARCOURS PROFESSIONNEL SYNTHESISOF RESEARCH WORKS APPENDIX

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.

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PARCOURS PROFESSIONNEL SYNTHESISOF RESEARCH WORKS APPENDIX PARCOURS PROFESSIONNEL SYNTHESISOF RESEARCH WORKS APPENDIX o a not Ψ channel equivalent the from SPO and CPO the ( estimate antenna to one possible considering it By makes phase. point access the of antennas I yteantenna the by i ( rpsdSolutions Proposed 2 = Rcie PKsmosbfr equalization. before symbols QPSK Received (a) etmtn h qiaetchannel equivalent the estimating 4. etmtn h qiaetpaecanl: channel phase equivalent the estimating 5. X symbol pilot precoded a sending 3. channel BB antenna the and estimating antenna reference 2. the between symbol pilot a sending 1. k tcnb enta h u fR hnesi osrcie ecnas oethat note also can We constructive. is channels RF of sum the that seen be can it 4.19, equation From coe calibration the applying By coe calibration study, our In two between transmission TR-OFDM SISO a performing that demonstrated has Kokar Y. thesis, his In with X transmitting After sol utpiaietr hc sol opsdo hs em t ouei ntr n does and unitary is module Its term. phase a of composed only is which term multiplicative a only is ) ff ,..., c pta focusing. spatial ect Q (Quadrature) N t fteacs on.T os,aclbainpaehsbe rpsdadcnit n: in consists and proposed been has phase calibration a so, do To point. access the of ) i fteacs on s: is point access the of i TR F hpte4 rmPwrMdln ohgl nryEfiin Devices Energy-Efficient highly to Modeling Power From 4. Chapitre I (phase) IGURE nteBB the on C P i ffi ( k H e SS TOD ihbt P n SPO. and CPO both with RT-OFDM SISO – 4.10 inscnb ietyotie rmtepaeo h qiaetchannel. equivalent the of phase the from obtained directly be can cients = ) Y( P ffi 1 i k → Φ srfrne PsadSO a eeautdfrec antenna each for evaluated be may SPOs and CPOs reference, as 1 = X( = ) insC cients X Ψ H e P eq i i TR ( P i k i H e p T ( → = ) ( k X = R k eq U = ) k X( = ) i ) e h inlta srcie yteue s: is user the by received is that signal the Ψ = P j e 2( i ( − H e k nteuln Fchannels RF uplink the on P φ Φ j ) 2 H k ∗ c P P e 1 eq X 1 z ( )(C − → φ ∗ 2xCPO i

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PARCOURS PROFESSIONNEL SYNTHESISOF RESEARCH WORKS APPENDIX hc ilb sdb BT oevaluate to Tx BB by used be will which than DL smaller and duration (UL a duration within frame occur time total must coherence frame) the the Therefore than channel. shorter duration the time a on only of estimate the channel complex propagation UL the estimation Channel : transmission UL RASK A. and OFDM of detailed. combination be the will modulation implement to aims 5 the of average the calculating in and n frame pilot per symbols 2. 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Tx Received Power [dBm] Received Power [dBm] F −62 −60 −58 −56 −54 −52 −50 −62 −61 −60 −59 −58 −57 −56 −55 −54 −53 IGURE 0 0

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ff 79 rn itne ewe h eev antennas. receive the between distances erent , 1]T uos .H M. Dubois, T. [14] 1]G .Sih Adrc eiaino igeatnarcpoiyrelation reciprocity single-antenna a of derivation direct “A Smith, S. G. [13] (UWB) ultra-wideband “Time-reversed Qiu, C. R. and Guo, N. Zhou, C. [10] 1]T uos .H M. Dubois, http://warpproject.org T. Available: [Online]. [12] project.” “Warp [11] 8 .Drd,P ox n .Fn,“outaosi iervra with reversal time acoustic “Robust Fink, M. for and Roux, transmission P. Derode, MIMO A. layered [8] “Dual Hanzo, L. and Masouros C. [7] H M. and Phan-Huy T. D. [6] 9 .E-alb,P yis,A ala,adG aaioau “Experimental Papanicolaou, G. and Paulraj, A. Kyritsi, P. El-Sallabi, H. [9] Received Power [dBm] Received Power [dBm] −64 −62 −60 −58 −56 −54 −52 −64 −62 −60 −58 −56 −54 −52 nentoa ypsu nProa,Ido,adMbl ai Com- Radio Mobile and (PIMRC) Indoor, in munications Personal, systems,” on Symposium MISO-OFDM International large to 2004. applied June 1568–1577, pp. 6, no. 52, vol. o h iedomain,” time the for spatial measured on based (MIMO) output multiple channels,” input multiple scattering,” multiple high-order nology efficiency,” bandwidth increased on Conference International IEEE in communications,” wireless reversal 2013. time Nov 4511–4523, pp. 9, no. 62, implementation vol. modulation,” “Practical Haas, H. spatial and Beach, of A. M. Grant, M. P. Wang, FMytm ur nevldsg,dmninn n synchronisation in and aspects,” dimensioning design, interval Guard OFDMsystem: 2009. 2884–2898, pp. in focusing time and Measurement space for communications,” precoding wireless reversal time on investigation 1995. 4206, p. 0 0

b FMsmo oue oadRx toward focused symbol OFDM (b) d FMsmo oue oadRx toward focused symbol OFDM (d) o.P,n.9,p.11 2015. 1–1, pp. 99, no. PP, vol. , 50 50 eiua ehooy EETascin on Transactions IEEE Technology, Vehicular ieesol eerhFrm WWRF-29) Forum, Research WirelessWorld o.5,n.6 p 5714,Jn 2010. June 1537–1543, pp. 6, no. 59, vol. , ∆ ∆ f f 2 4 lr,adM Crussi M. and elard, OFDM SymbolIndex OFDM SymbolIndex ´ 100 100 lr,M Crussi M. elard, ´ EETascin nAtna n Propagation and Antennas on Transactions IEEE et21,p.896–901. pp. 2013, sept , EETascin nVhclrTechnology Vehicular on Transactions IEEE EETascin nIsrmnainand Instrumentation on Transactions IEEE 150 150 lr,“eev nen hf eigfor keying shift antenna “Receive elard, ´ hsclrve letters review Physical EETascin nVhclrTech- Vehicular on Transactions IEEE ue21,p.4852–4856. pp. 2012, June , r,adI az Tm reversal “Time Maaz, I. and ere, ` 200 200 r,“iervra naMISO a in reversal “Time ere, ` omnctos(C) 2012 (ICC), Communications 2 4 Rx4 Rx3 Rx2 Rx1 Rx4 Rx3 Rx2 Rx1 03IE 4hAnnual 24th IEEE 2013 250 250

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PARCOURS PROFESSIONNEL SYNTHESISOF RESEARCH WORKS PPENDIX A ,

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PARCOURS PROFESSIONNEL SYNTHESISOF RESEARCH WORKS APPENDIX

Lla ose,GyGgit n an ulsn yaial ofiual euiyfor security configurable Dynamically Burleson. Wayne and Gogniat, Guy Bossuet, Lilian Using Machines Virtual Interactive And Best. Batch Joel Mixing [BGB06] : VSched Dinda. P.A. and Lin Bin [Bes13] [BD05] [BCLK [BBFH [BBC [ARW Je [Arn95] O rod .Rctr .Ftwi,adO lm.Pwrcnupinmdln fdif- of modeling consumption Power Blume. O. and Fettweis, G. Richter, F. Arnold, O. [ARFB10] [APA B ma . .B od n .Mhma.Ie 0.1bsdvria advrin handover vertical based 802.21 Ieee Muhammad. I. and Mohd, B. D. Handbook. A., 2015. 4 Ammar May. introduction, B. builder Dsp Inc. Altera [AMM12] Guide Altera. User 2014. July guide, user [Alt15b] estimator power early Powerplay Incorporation. [Alt15a] Altera 2015. paper. white 5g Alliance. NGMN [Alt14b] Aichouch. [All15b] Mehdi El Mohamed [Aic14a] hetero- in decisions handover vertical Enabling Gaiti. D. [AHK and Boulahia, L.M. Ahmed, A. [ABG14] Nse .Aoab n aiS lael erlntokbsdhnoe management handover based network neural A Alwakeel. S. Sami and Alotaibi M. Nasser [AA16] + + + + BönB rnebr,ArnD lc,Jh .Clnrn,Uaaewr ei Henna- Devi, UmaMaheswari Calandrino, M. John Block, D. Aaron Brandenburg, B. Björn 07] JsnArn elyPc,Ei nesn ai nrw,E op o as Fabrice Sass, Ron Komp, Ed Andrews, David Anderson, Erik Peck, Wesley Agron, Jason 06a] + + AdesAn,Mru ap,AdesKle,En ubr,Brhr ltnr Marco Plattner, Bernhard Lubbers, Enno Keller, Andreas Happe, Markus Agne, Andreas 14] N use,M ihrsn ..Wlig,K idl,adA un.Apyn e schedu- new Applying Burns. A. and Tindell, K. Wellings, A.J. Richardson, M. Audsley, N. 10] H rul .Brte .FüyHrr,J uune,D inle,adH oso.Tcet Tic Boisson. H. and Vignolles, D. Cueugniet, J. Flüry-Hérard, B. Burette, D. Breuil, H. 08] SeaoBzi .Ci-i,TiryE li,H icn or hnagYn,adAlessio and Yang, Chenyang Poor, Vincent H. Klein, E. Thierry Chih-Lin, I. Buzzi, Stefano 16] ieSsesSmoim 06 TS0.2t EEInternational IEEE 27th RTSS’06. 2006. Symposium, Systems Time RMFG bitstreams. FPGA SRAM 2013. Guelph, of Engineering,University of School thesis, PhD 2005. Scheduling. Real-time Periodic Communications in Areas Selected on Journal energy-e IEEE of survey A Zappone. l’Information. de Technologies des du Général et Conseil l’Environnement le de Général et Conseil Durable du Développement Rapport 2008. Déc. durable, 2007. développement report, status A : rt Litmus Anderson. H. James and Leontyev, diy igter osai roiypeepiescheduling. pre-emptive priority static to theory ling 1995. eetbs tto ye nhtrgnosclua ewrs In networks. cellular 2010 heterogeneous Summit, in types station base ferent In chip. on systems cpu/fpga hybrid for services Run-time Stevens. Jim and Baijot, 4–4,Mrh2012. March 140–144, i n ia ewrs In networks. wimax and wifi UG-01070. techniques allocation resources RTOS’s 2014. an May of Rennes, de configuration and system chine classification. a and Tutorials state-of-the-art & A Surveys : networks wireless geneous ltnr n hita lsl eoo noeaigsse prahfrreconfigurable for approach system operating An : computing. Reconos Plessl. Christian and Platzner, ec nMcieLann n plctos CL 2015 ICMLA Applications, and Learning Machine on In rence networks. heterogeneous for strategy ff e .Anl.Tesls otaeenvironment. software 2 splash The Arnold. M. rey yln eieOverview Device V Cyclone elTm prtn ytmHrwr xeso oefrSse-nCi Designs System-on-Chip for Core Extension Hardware System Operating Real-Time ir,IEEE Micro, ae –,Jn 2010. June 1–8, pages , 62 7681 2014. :776–811, 16(2) , 41 6–1 2014. :60–71, 34(1) , nentoa ora fEbde Systems Embedded of Journal International 02IE ypsu nCmuesIfrais(ISCI) Informatics Computers on Symposium IEEE 2012 ffi leaCroain 2015. Corporation, Altera . in ehiusfr5 ewrsadcalne ahead. challenges and networks 5G for techniques cient vlaino utpeciiaiyra-ievrulma- virtual real-time criticality multiple a of Evaluation 99 rceig 05IE 4hItrainlConfe- International 14th IEEE 2015 - Proceedings 2016. , otaeEgneigJournal Engineering Software 2016. , .Supercomput. J. Bibliography uueNtokadMobile and Network Future ae –2 EE 2006. IEEE, 3–12. pages , 2006. , EECommunications IEEE 2720 May :277–290, 9 , hss INSA Theses, . 2010. , pages , Real- .

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PARCOURS PROFESSIONNEL SYNTHESISOF RESEARCH WORKS APPENDIX PARCOURS PROFESSIONNEL SYNTHESISOF RESEARCH WORKS APPENDIX Emne Huck. Emmanuel [Huc11] [HSH [HRR Gro esradBnLsi.Teol irvsr:cnegnepito irkresand microkernels of point convergence : microvisor okl4 The Leslie. [HLF Ben and Heiser Gernot [HL10] E Nebel. Wolfgang and Reinkemeier, Philipp Kleen, Henning Hartmann, A. rea- Philipp for services system operating Real-time Huss. [HKRN08] S.A. and Klaus, Stephan Hastono, Prih [HKH04] Cu-sa un n a-n sug adaersuc itaiainfrdynami- for virtualization resource Hardware Hsiung. Pao-Ann and Huang Chun-Hsian [HH09] and In dynamic Fast bother? Becker. why Jürgen and : Noguera, systems Juanjo embedded Göhringer, Virtualizing Diana Hübner, Michael Heiser. Gernot [HGNB10] [Hei] DeHon. Andre and Hauck Scott [HDL defi- software for techniques reconfiguration partial [HD10] dynamic of evaluation Performance Tar- and Generation Automatic Jerraya. Amine Ahmed [Has16] and Yoo, Sungjoo level Gauthier, Lovic system for modeling RTOS Gajski. D. Daniel [GYJ01] and Yu, Haobo Gerstlauer, Andreas [GYG08] [GRE + + + + + Ce-e s,JaL io hnCinFn,Ci-he eg h-uHag Wen-Tsan Huang, Shi-Yu Weng, Chia-Chien Fang, Shan-Chien Liao, Jia-Lu Hsu, Chen-Wei 11] MthwRGtas Je Guthaus, R Matthew 01] J .Hag .B u,S .Ho .J ak .M y,S .Pr,adC .Km e nam: arm on Xen Kim. R. C. and Park, Y. S. Ryu, M. J. Park, J. C. Heo, K. S. Suh, B. S. Hwang, Y. J. 08a] FbaoHse,VtrMRs,Io es vIiag,ProAer,CsrAMMarcon, M A César Alegre, Porto Ipiranga, Av Reis, M Igor Rosa, M Vitor Hessel, Fabiano 04] E ug .J ai,J .Lvn,E .Sot .Y .Cen,adG .Constantinides. A. G. and Cheung, K. Y. P. Stott, A. E. Levine, M. J. Davis, J. J. Hung, E. 16] ytmvrulzto sn e yevsrframbsdscr oiepoe.In Conference phones. Networking mobile and secure Communications arm-based Consumer IEEE for 5th hypervisor xen using virtualization System pc xlrto nhtrgnosMSCarchitectures 2011. 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