Network Defined Vehicle v.s. Software Defined Vehicle, Ethernet(38)

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Search result on Software Defined Vehicle

MOVESTAR: An Open-Source Vehicle Fuel and Emission Model based on USEPA MOVES

[1] United States Environmental Protection Agency. Sources of greenhouse gas emis- sions, Accessed: 2020-08-06. URL https://www.epa.gov/ghgemissions/ sources-greenhouse-gas-emissions.
[2] J. N. Barkenbus. Eco-driving: An overlooked climate change initiative. Energy policy, 38(2): 762–769, 2010.
[3] M. Sivak and B. Schoettle. Eco-driving: Strategic, tactical, and operational decisions of the driver that influence vehicle fuel economy. Transport Policy, 22:96–99, 2012.
[4] M. Barth and K. Boriboonsomsin. Energy and emissions impacts of a freeway-based dynamic eco-driving system. Transportation Research Part D: Transport and Environment, 14(6):400 – 410, 2009. ISSN 1361-9209. doi:https://doi.org/10.1016/j.trd.2009.01.004. URL http:// www.sciencedirect.com/science/article/pii/S1361920909000121. The interaction of environmental and traffic safety policies.
[5] M. Barth, S. Mandava, K. Boriboonsomsin, and H. Xia. Dynamic eco-driving for arterial corridors. In 2011 IEEE Forum on Integrated and Sustainable Transportation Systems, pages 182–188, June 2011. doi:10.1109/FISTS.2011.5973594.
[6] K. Katsaros, R. Kernchen, M. Dianati, and D. Rieck. Performance study of a green light op- timized speed advisory (glosa) application using an integrated cooperative its simulation plat- form. In 2011 7th International Wireless Communications and Mobile Computing Conference, pages 918–923, July 2011. doi:10.1109/IWCMC.2011.5982524.
[7] O. D. Altan, G. Wu, M. J. Barth, K. Boriboonsomsin, and J. A. Stark. Glidepath: Eco-friendly automated approach and departure at signalized intersections. IEEE Transactions on Intelligent Vehicles, 2(4):266–277, Dec 2017. ISSN 2379-8904. doi:10.1109/TIV.2017.2767289.
[8] P.Hao,G.Wu,K.Boriboonsomsin,andM.J.Barth.Eco-approachanddeparture(ead)applica- tion for actuated signals in real-world traffic. IEEE Transactions on Intelligent Transportation Systems, 20(1):30–40, Jan 2019. ISSN 1524-9050. doi:10.1109/TITS.2018.2794509.
[9] Z. Wang, Y. Hsu, A. Vu, F. Caballero, P. Hao, G. Wu, K. Boriboonsomsin, M. J. Barth, A. Kailas, P. Amar, E. Garmon, and S. Tanugula. Early findings from field trials of heavy- duty truck connected eco-driving system. In 2019 IEEE Intelligent Transportation Systems Conference (ITSC), pages 3037–3042, 2019.
[10] United States Environmental Protection Agency. MOVES and other mobile source emissions models, Accessed: 2020-08-04. URL https://www.epa.gov/moves.
[11] United States Environmental Protection Agency. MOVES2014a user interface reference man- ual, Accessed: 2020-08-06. URL https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey= P100Q3C1.pdf.
[12] United States Environmental Protection Agency. Using MOVES for estimating state and local inventories of onroad greenhouse gas emissions and energy consumption, Accessed: 2020-08-06. URL http://www.ourenergypolicy.org/wp-content/uploads/2016/ 09/P100OW0B.pdf.
[13] UnitedStatesEnvironmentalProtectionAgency.Exhaustemissionratesforheavy-dutyonroad vehicles in moves201x, Accessed: 2020-08-09. URL https://cfpub.epa.gov/si/si_ public_record_report.cfm?Lab=OTAQ&dirEntryId=328830.
[14] J. Warila, E. Nam, L. Landman, and A. Kahan. Light-duty exhaust emission rates in moves2010, Accessed: 2020-08-10. URL http://citeseerx.ist.psu.edu/viewdoc/ download;jsessionid=AAE023D542E3688088AD383D57B1BE19?doi=10.1.1.360. 5490&rep=rep1&type=pdf.
[15] MathWorks. Matlab, Accessed: 2020-08-10. URL https://www.mathworks.com/ products/matlab.html?s_tid=hp_products_matlab.
[16] PTV GROUP. PTV Vissim is the world’s most advanced and flexible traffic simulation software, Accessed: 2020-08-10. URL https://www.ptvgroup.com/en/solutions/ products/ptv-vissim/.
[17] Z. Wang, G. Wu, and M. J. Barth. Cooperative eco-driving at signalized intersections in a partially connected and automated vehicle environment. IEEE Transactions on Intelligent Transportation Systems, 21(5):2029–2038, 2020.

Energy-Aware Graph Task Scheduling in Software-Defined Air-Ground Integrated Vehicular Networks

[1] M. A. Messous, S. M. Senouci, H. Sedjelmaci, and S. Cherkaoui, “A game theory based efficient computation offloading in an UAV network,” IEEE Trans. Veh. Technol., vol. 68, no. 5, pp. 4964–4974, 2019.
[2] Z. Guan, N. Cen, T. Melodia, and S. M. Pudlewski, ”Distributed Joint Power, Association and Flight Control for Massive-MIMO Self-Organizing Flying Drones,” IEEE/ACM Trans. Netw., vol. 28, no. 4, pp. 1491–1505, 2020.
[3] A. Trotta, U. Muncuk, M. Di Felice, and K. R. Chowdhury, “Per- sistent Crowd Tracking Using Unmanned AerIal Vehicle Swarms: A Novel Framework for Energy and Mobility Management,” IEEE Veh. Technol. Mag.., vol. 15, no. 2, pp. 96–103, 2020.
[4] G. Secinti, A. Trotta, S. Mohanti, M. Di Felice, and K. R. Chowd- hury, ”FOCUS: Fog Computing in UAS Software-Defined Mesh Networks,” IEEE Trans. Intell. Transp. Syst., vol. 21, no. 6, pp. 2664- 2674, 2020.
[5] S. Jacek, “Fukushima Plants Radiation Levels Monitored with an UAV,” https://theaviationist. com/2014/01/29/fukushima- japan-uav/, Jan. 29. 2014.
[6] L. Abend, “Pilot: The mystery of Kobe Bryant’s chopper crash,” https://www. cnn. com/2020/01/28/opinions/kobe- bryant-helicopter-crash-abend/index. html, Jan. 28. 2020.
[7] M. Krznar, P.Piljek, D. Kotarski, and D. Pavkovic ́, “Modeling, Control System Design and Preliminary Experimental Verification of a Hybrid Power Unit Suitable for Multirotor UAVs,” Energies, vol. 14, no. 9, pp. 1–24, 2021.
[8] M. Liwang, Z. Gao, and X. Wang, “Let’s Trade in the Future! A Futures-Enabled Fast Resource Trading Mechanism in Edge Computing-Assisted UAV Networks,” IEEE J. Selected Areas in Commun., vol. 39, no. 11, pp. 3252–3270, 2021.
[9] M. Liwang, S. Hosseinalipour, Z. Gao, Y. Tang, L. Huang, and H. Dai, “Allocation of computation-intensive graph jobs over vehicular clouds in IoV,” IEEE Internet Things J., vol. 7, no. 1, pp. 311–324, 2019.
[10] M. Liwang, Z. Gao, S. Hosseinalipour, and H. Dai, “Multi-task offloading over vehicular clouds under graph-based representa- tion,” IEEE Int. Conf. Commun. (ICC), Dublin, Ireland, Jun. 2020, pp. 1–7.
[11] R. Florin, A. Ghazizadeh, P. Ghazizadeh, S. Olariu, and D. C. Marinescu, ”Enhancing Reliability and Availability through Re- dundancy in Vehicular Clouds,” IEEE Trans. Cloud Comput., vol. 9, no. 3, pp. 1061–1074, 2021.
[12] N. Zhang, S. Zhang, P. Yang, O. Alhussein, W. Zhuang, and X. Shen, “Software defined space-air-ground integrated vehicular networks: challenges and solutions,” IEEE Commun. Mag., vol. 55, no. 7, pp. 101–109, 2017.
[13] Y. Wang, W. Chen, T. H. Luan, Z. Su, Q. Xu, R. Li, and N. Chen ”Task Offloading for Post-Disaster Rescue in Un- manned Aerial Vehicles Networks,” IEEE/ACM Trans. Netw., DOI: 10.1109/TNET.2022.3140796, pp. 1–1, 2022.
[14] F. Lyu, P. Yang, H. Wu, C. Zhou, J. Ren, Y. Zhang, and X. Shen”Service-Oriented Dynamic Resource Slicing and Optimiza- tion for Space-Air-Ground Integrated Vehicular Networks,” IEEE Trans. Intell. Transp. Syst., pp.1–1, 2021.
[15] K. Wang, H. Yin, W. Quan, and G. Min, “Enabling collaborative edge computing for software defined vehicular networks,” IEEE Netw., vol. 32, no. 5, pp. 112–117, 2018.
[16] X. Hou, Z. Ren, J. Wang, W. Cheng, Y. Ren, K. C. Chen, and H. Zhang, ”Reliable Computation Offloading for Edge-Computing- Enabled Software-Defined IoV,” IEEE Internet Things J., vol. 7, no. 8, pp. 7097–7111, 2020.
[17] G. Luo, H. Zhou, N. Cheng, Q. Yuan, F. Yang, and X. Shen, “Software defined cooperative data sharing in edge comput- ing assisted 5G-VANET,” IEEE Trans. Mobile Comput., DOI: 10.1109/TMC.2019.2953163, pp. 1–1, 2019.
[18] J. Ghaderi, S. Shakkottai, and R. Srikant, “Scheduling storms and streams in the cloud,” ACM Trans. Modeling and Performance Eval. of Comput. Syst., vol. 1, no. 4, pp. 1–14, 2016.
[19] M. Shafiee and J. Ghaderi, ”Scheduling Coflows With Dependency Graph,” IEEE/ACM Trans. Netw., DOI: 10.1109/TNET.2021.3116133, pp.1–1, 2021.
[20] J. Yu, X. Hao, Z. Cui, P. He, and T. Liu, “Boosting Fairness for Masked Face Recognition,”Proc. IEEE/CVF Int. Conf. Computer Vision (ICCV) Workshops, Virtual, Oct. 2021, pp. 1531–1540.
[21] V. Carletti, P. Foggia, A. Saggese, and M. Vento, “Challenging the time complexity of exact subgraph isomorphism for huge and dense graphs with VF3,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 40, no. 4, pp. 804–818, 2018.
[22] Z. Gao, M. Liwang, S. Hosseinalipour, H. Dai, and X. Wang, “A truthful auction for graph job allocation in vehicular cloud-assisted networks,” IEEE Trans. Mobile Comput., DOI: 10.1109/TMC.2021.3059803, pp. 1–1, 2021.
[23] T. Bai, J. Wang, Y. Ren, and L. Hanzo, “Energy-efficient compu- tation offloading for secure uav-edge-computing systems,” IEEE Trans. Veh. Technol., vol. 68, no. 6, pp. 6074–6087, 2019.
[24] A. Sacco, F. Esposito, G. Marchetto and P. Montuschi, ”A Self- Learning Strategy for Task Offloading in UAV Networks,” IEEE Trans. Veh. Technol., doi: 10.1109/TVT.2022.3144654, pp. 1–1, 2022.
[25] Z.Yan,P.Cheng,Z.Chen,B.Vucetic,andY.Li,”Two-Dimensional Task Offloading for Mobile Networks: An Imitation Learning Framework,” IEEE/ACM Trans. Netw., vol. 29, no. 6, pp. 2494-2507, 2021.
[26] H. Tout, A. Mourad, N. Kara and C. Talhi, ”Multi-Persona Mobil- ity: Joint Cost-Effective and Resource-Aware Mobile-Edge Com- putation Offloading,” IEEE/ACM Trans. Netw., vol. 29, no. 3, pp. 1408-1421, 2021.
[27] P. A. Apostolopoulos, E. E. Tsiropoulou and S. Papavassiliou, ”Risk-Aware Data Offloading in Multi-Server Multi-Access Edge Computing Environment,” IEEE/ACM Trans. Netw., vol. 28, no. 3, pp. 1405–1418, 2020.
[28] S. Hosseinalipour, A. Nayak, and H. Dai, “Power-aware allocation of graph jobs in geo-distributed cloud networks,” IEEE Trans. Parallel Distrib. Syst., vol. 31, no. 4, pp. 749–765, 2019.
[29] M. Liwang, Z. Gao, S. Hosseinalipour, H. Dai, and X. Wang, “Energy-aware allocation of graph jobs in vehicular cloud computing-enabled software-defined IoV,” IEEE Int. Conf. Comput. Commun. Workshops (INFOCOM WKSHPS), Toronto, ON, Canada, July. 2020, pp. 1–6.
[30] Y. Sahni, J. Cao, L. Yang, and Y. Ji, ”Multihop Offloading of Multiple DAG Tasks in Collaborative Edge Computing,” IEEE Internet Things J., vol. 8, no. 6, pp. 4893–4905, 2021.
[31] L. Shi, Z. Zhang, and T. Robertazzi, “Energy-aware scheduling of embarrassingly parallel jobs and resource allocation in cloud,” IEEE Trans. Parallel Distrib. Syst., vol. 28, no. 6, pp. 1607–1620, 2017.
[32] M. Goudarzi, M. Zamani, and A. T. Haghighat, “A fast hybrid multi-site computation offloading for mobile cloud computing,” Journal of Netw. Comput. Appl., vol. 66, pp. 219–231, 2017.
[33] Y. Geng, Y. Yang, and G. Cao, “Energy-efficient computation offloading for multicore-based mobile devices,” IEEE Int. Conf. Comput. Commun. (INFOCOM), Honolulu, HI, USA, Apr. 2018, pp. 1–6.
[34] F. Sun, F. Hou, N. Cheng, M. Wang, H. Zhou, L. Gui, and X. Shen, “Cooperative task scheduling for computation offloading in vehicular cloud,” IEEE Trans. Veh. Technol., vol. 67, no. 11, pp: 11049–11061, 2018.
[35] P. Kurp, “Green computing,” Commun. ACM, vol. 51, no. 10, pp. 11–13, 2008.
[36] X. Zhu, Y. Li, D. Jin, and J. Lu, “Contact-aware optimal resource allocation for mobile data offloading in opportunistic vehicular networks,” IEEE Trans. Veh. Technol., vol. 66, no. 8, pp. 7384–7399, 2017.
[37] Q. Song, F. C. Zheng, Y. Zeng, and J. Zhang, “Joint beamforming and power allocation for UAV-enabled full-duplex relay,” IEEE Trans. Veh. Technol., vol. 68, no. 2, pp. 1657–1671, 2018.
[38] A. A. Khuwaja, Y. Chen, N. Zhao, M. S. Alouini, and P. Dobbins, “A survey of channel modeling for uav communications,” IEEE Commun. Surveys Tut., vol. 20, no. 4, pp. 2804–2821, 2018.
[39] X. Chen, L. Jiao, W. Li, and X. Fu, “Efficient multi-user compu- tation offloading for mobile-edge cloud computing,” IEEE/ACM Trans. Netw., vol. 24, no. 5, pp. 2795–2808, 2016.
[40] A. Bazzi, C. Campolo, B. M. Masini, A. Molinaro, A. Zanella, and A. O. Berthet, “Enhancing cooperative driving in IEEE 802.11 ve- hicular networks through full-duplex radios,” IEEE Trans. Wireless Commun., vol. 17, no. 4, pp. 2402–2016, 2018.
[41] Y.Mao,J.Zhang,andK.B.Letaief,“Jointtaskoffloadingschedul- ing and transmit power allocation for mobile-edge computing systems,” IEEE Int. Conf. Commun. Netw. (WCNC), San Francisco, CA, USA, Mar. 2017, pp. 1–6.
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On the Security of Networked Control Systems in Smart Vehicle and its Adaptive Cruise Control

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[8] N. Toorchi, M. A. Attari, M. S. Haghighi, and Y. Xiang, “A markov model of safety message broadcasting for vehicular networks,” in IEEE Wireless Communications and Networking Conference (WCNC), 2013, pp. 1657–1662.
[9] M. Harris, “Researcher hacks self-driving car sensors,” IEEE Spectrum, vol. 9, p. , 2015.
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[13] A. O. de Sa ́, L. F. R. da Costa Carmo, and R. C. Machado, “Covert attacks in cyber-physical control systems,” IEEE Trans- actions on Industrial Informatics, vol. 13, no. 4, pp. 1641–1651, 2017.
[14] P. Shakouri, A. Ordys, D. S. Laila, and M. Askari, “Adaptive cruise control system: comparing gain-scheduling pi and lq controllers,” IFAC Proceedings Volumes, vol. 44, no. 1, pp. 12 964–12 969, 2011.
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[18] Y. Liu, P. Ning, and M. K. Reiter, “False data injection attacks against state estimation in electric power grids,” ACM Trans- actions on Information and System Security (TISSEC), vol. 14, no. 1, p. 13, 2011.
[19] R. Deng, P. Zhuang, and H. Liang, “False data injection attacks against state estimation in power distribution systems,” IEEE Transactions on Smart Grid, vol. 10, no. 3, pp. 2871–2881, 2018.
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Enable an Open Software Defined Mobility Ecosystem through VEC-OF

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A Language for Autonomous Vehicles Testing Oracles

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SD-FFR: Software Defined Fast Failure Recovery Mechanism in the Automatic Warehouse

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Application Layer Modeling in Vehicle Networks: Cooperative Maneuver Use Case

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SD-VEC: Software-Defined Vehicular Edge Computing with Ultra-Low Latency

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Stable and Efficient Shapley Value-Based Reward Reallocation for Multi-Agent Reinforcement Learning of Autonomous Vehicles

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TOWARDS FORMALIZATION AND MONITORING OF MICROSCOPIC TRAFFIC PARAMETERS USING TEMPORAL LOGIC

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Simulation-based Evaluation of a Synchronous Transaction Model for Time-Sensitive Software-Defined Networks

[1] J. Cui, S. Zhou, H. Zhong, Y. Xu, and K. Sha. Transaction-Based Flow Rule Conflict Detection and Resolution in SDN. In 2018 27th International Conference on Computer Communication and Networks (ICCCN), pages 1–9, July 2018.
[2] M. Curic, Z. Despotovic, A. Hecker, and G. Carle. Transactional Network Updates in SDN. In 2018 European Conference on Networks and Communications (EuCNC), pages 203–208, 2018.
[3] R. Enns, M. Bjorklund, J. Schoenwaelder, and A. Bierman. Network Configuration Protocol
(NETCONF). RFC 6241, IETF, June 2011.
[4] Timo Ha ̈ckel, Philipp Meyer, Franz Korf, and Thomas C. Schmidt. SDN4CoRE: A Simulation
Model for Software-Defined Networking for Communication over Real-Time Ethernet. In Meyo Zongo, Antonio Virdis, Vladimir Vesely, Zeynep Vatandas, Asanga Udugama, Koojana Kula- dinithi, Michael Kirsche, and Anna Fo ̈rster, editors, Proc. of the 6th Int. OMNeT++ Community Summit 2019, volume 66 of EPiC Series in Computing, pages 24–31. EasyChair, December 2019.
[5] Timo Ha ̈ckel, Philipp Meyer, Franz Korf, and Thomas C. Schmidt. Software-Defined Networks Supporting Time-Sensitive In-Vehicular Communication. In 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring), pages 1–5, Piscataway, NJ, USA, April 2019. IEEE Press.
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[10] Philipp Meyer, Franz Korf, Till Steinbach, and Thomas C Schmidt. Simulation of Mixed Critical In-vehicular Networks. In Recent Advances in Network Simulation, pages 317–345. Springer, 2019.
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参考資料　ベクタージャパン

「はじめての」シリーズ　 ベクタージャパン　＜エンジニア夏休み企画>【読書感想文】
https://qiita.com/kaizen_nagoya/items/2e41634f6e21a3cf74eb

必須

「はじめてのCAN/CANFD 」 ベクタージャパン　＜エンジニア夏休み企画>【読書感想文】
https://qiita.com/kaizen_nagoya/items/1fee270be00ef90ca4ec

はじめてのAUTOSAR(classic platform)　＜エンジニア夏休み企画>【読書感想文】
https://qiita.com/kaizen_nagoya/items/696ad320f76f284664d7

「はじめての診断」 ベクタージャパン　＜エンジニア夏休み企画>【読書感想文】
https://qiita.com/kaizen_nagoya/items/36b5ab0fb163f2adea07

「はじめてのCANoe」 ベクタージャパン ＜エンジニア夏休み企画>【読書感想文】
https://qiita.com/kaizen_nagoya/items/ec4eaafd381656e24117

「はじめての車載Ethernet 」 ベクタージャパン　＜エンジニア夏休み企画>【読書感想文】
https://qiita.com/kaizen_nagoya/items/97a6d755af9a2790e972

「はじめてのCANoe.Ethernet」 ベクタージャパン ＜エンジニア夏休み企画>【読書感想文】
https://qiita.com/kaizen_nagoya/items/898a2deb94452c6d690b

推奨

「はじめてのAUTOSAR SecOC」 ベクタージャパン　＜エンジニア夏休み企画>【読書感想文】
https://qiita.com/kaizen_nagoya/items/c6513662968e97d4f65e

「はじめてのSOME/IP」 ベクタージャパン　＜エンジニア夏休み企画>【読書感想文】
https://qiita.com/kaizen_nagoya/items/2a7a5d1c797fd13b060f

「はじめてのXCP」 ベクタージャパン　＜エンジニア夏休み企画>【読書感想文】
https://qiita.com/kaizen_nagoya/items/7ec2e31efb99d39e900c

「はじめてのCAPL」 (Communication Access Programming Language) ベクタージャパン　＜エンジニア夏休み企画>【読書感想文】
https://qiita.com/kaizen_nagoya/items/990383db16051739ca12

「はじめてのLIN」ベクタージャパン　＜エンジニア夏休み企画>【読書感想文】
https://qiita.com/kaizen_nagoya/items/e7687a80c965b486ba0d

「はじめてのJ1939」 ベクタージャパン　＜エンジニア夏休み企画>【読書感想文】
https://qiita.com/kaizen_nagoya/items/983c69c8f33ef24b7a3d

「はじめてのCANape」 ベクタージャパン ＜エンジニア夏休み企画>【読書感想文】
https://qiita.com/kaizen_nagoya/items/ae44c217b2db1e1e7ec1

参考

「はじめてのCANalyzer」 ベクタージャパン ＜エンジニア夏休み企画>【読書感想文】
https://qiita.com/kaizen_nagoya/items/83d6b8e494988c1da76e

「はじめてのFlexRay 」 ベクタージャパン＜エンジニア夏休み企画>【読書感想文】
https://qiita.com/kaizen_nagoya/items/e6e97354734e5daaec8b

「はじめての単体試験」 ベクタージャパン＜エンジニア夏休み企画>【読書感想文】
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「はじめてのvectorCAST」 ベクタージャパン＜エンジニア夏休み企画>【読書感想文】
https://qiita.com/kaizen_nagoya/items/cc30b72496aeaae53159

「はじめてのvTESTstudio」 ベクタージャパン ＜エンジニア夏休み企画>【読書感想文】
https://qiita.com/kaizen_nagoya/items/c1cc5b091bfd76e72128

自己参照

詳解 車載ネットワーク CAN、CAN FD、LIN、CXPI、Ethernetの仕組みと設計のために
https://qiita.com/kaizen_nagoya/items/44a9e6b0f5363b4a5b35

詳解 車載ネットワーク CAN, CAN FD, LIN, CXPI, Ethernetの仕組みと設計のために(2)参考文献 ＜エンジニア夏休み企画>【読書感想文】
https://qiita.com/kaizen_nagoya/items/e156cbdd5fce9263776e

AUTOSAR 「完全に理解した」
https://qiita.com/kaizen_nagoya/items/51983798ad7902b33cb1

A big wrapping cloth with the miniature garden
https://qiita.com/kaizen_nagoya/items/96411f20632e7f3ff73a

Network Defined Vehicle
https://qiita.com/kaizen_nagoya/items/a696f8a8cbd141215266

Network Defined Vehicle v.s. Software Defined Vehicle
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AUTOSAR文書を読む前に知っているとよいこと。
https://qiita.com/kaizen_nagoya/items/87685d872431751b2d0c

プログラマが知っていると良い「公序良俗」
https://qiita.com/kaizen_nagoya/items/9fe7c0dfac2fbd77a945

権利と義務の前に。仮説（147）
https://qiita.com/kaizen_nagoya/items/47d4e992d0fd340403fd

物理記事　上位100
https://qiita.com/kaizen_nagoya/items/66e90fe31fbe3facc6ff

数学関連記事１００
https://qiita.com/kaizen_nagoya/items/d8dadb49a6397e854c6d

言語・文学記事　１００
https://qiita.com/kaizen_nagoya/items/42d58d5ef7fb53c407d6

医工連携関連記事一覧
https://qiita.com/kaizen_nagoya/items/6ab51c12ba51bc260a82

通信記事１００
https://qiita.com/kaizen_nagoya/items/1d67de5e1cd207b05ef7

自動車　記事　１００
https://qiita.com/kaizen_nagoya/items/f7f0b9ab36569ad409c5

Ethernet 記事一覧　Ethernet(0)
https://qiita.com/kaizen_nagoya/items/88d35e99f74aefc98794

＜この記事は個人の過去の経験に基づく個人の感想です。現在所属する組織、業務とは関係がありません。＞
This article is an individual impression based on the individual's experience. It has nothing to do with the organization or business to which I currently belong.

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