Computer Science ›› 2018, Vol. 45 ›› Issue (6): 166-171.doi: 10.11896/j.issn.1002-137X.2018.06.029

• Software & Database Technology • Previous Articles     Next Articles

Nash Equilibrium Based Method for Mapping AUTOSAR Tasks to Multicore ECU

RAN Zheng, LUO Lei, YAN Hua, LI Yun   

  1. School of Computer Science and Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China
  • Received:2017-05-16 Online:2018-06-15 Published:2018-07-24

Abstract: With the growing requirements of automotive applications on processing power,the electronic control units (ECUs) in modern automotive system escalates to multicore architecture.The design,implementation and integration of AUTOSAR applications in multicore ECU will face new challenges.One of these challenges is mapping the tasks to multicore ECU while the real-time performance of system is ensured.In addition,the resource limitation and scheduling analysis in real-time system make the problems more complex in AUTOSAR static configuration.So this paper proposed a Nash equilibrium based method for mapping AUTOSAR tasks to multicore ECU.This method has important practical significance in improving the efficiency of task mapping process by applying the priority of tasks in game process.Finally,the proposed method was applied to the automotive electronic instance in AUTOSAR.The experimental results show that the proposed method has good performance in the worst case response time of the runnable entities in each task.

Key words: AUTOSAR, Multicore ECU, Nash equilibrium, Task mapping

CLC Number: 

  • TP37
[1]AUTOSAR.autosar standards[EB/OL].
[2]URBINA M,OBERMAISSER R.Multi-Core Architecture for AUTOSAR based on Virtual Electronic[C]//IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA).2015.
[3]URBINA M,AHMADIAN H,OBERMAISSER R.Co-simulation Framework for AUTOSAR Multi-Core Processors with Message-based Network-on-Chips[C]//2016 IEEE 14th International Conference on Industrial Informatics (INDIN).2016.
[4]CHEN Y J,CHANG W W,LIU C Y,et al.Processors Allocation for MPSoCs With Single ISA Heterogeneous Multi-Core Architecture[J].IEEE Access,2017(5):4028-4036.
[5]MAKASARWALA H A,HAZARI P.Using genetic algorithm for load balancing in cloud computing[C]//8th International Conference on Electronics,Computers and Artificial Intelligence (ECAI).2016.
[6]KAUR P,AGNIHOTRI M.Efficient Variable Neighborhood Search Performance Based Joint Optimization Task Allocation for Multicore Processor[C]//2nd International Conference on Contemporary Computing and Informatics (IC3I).2016.
[7]FARAGARDI H R,LISPER B,SANDSTROM K,et al.An Efficient Scheduling of AUTOSAR Runnables to Minimize Communication Cost in Multicore Systems[C]//7th International Symposium on Telecommunications.2014:41-48.
[8]TRIPATHI R,VIGNESH S,TAMARAPALLI V,et al.Non-cooperative power and latency aware load balancing in distributed data centers[J].Journal of Parallel and Distributed Computing,2017,107:76-86.
[9]JIANG Y C.A Survey of Task Allocation and Load Balancing in Distributed Systems[J].IEEE Transactions on Parallel and Distributed Systems,2016,27(2):585-599.
[10]AUTOSAR P.Specification of RTEV3.1.0R4.0 Rev 2 [S/OL].
[11]SAIDI S E,COTARD S,CHAABAN K,et al.An ILP approach for mapping AUTOSAR runnables on multi-core architectures[C]//Proceedings of the 2015 Workshop on Rapid Simulation and Performance Evaluation:Methods and Tools.2015.
[12]AUTOSAR P.Specification of Operating System (V4.1.0 R4.0 Rev 2) [OL].
[13]ASLAM S,SHAH M A.Load Balancing Algorithms in Cloud Computing:A Survey of Modern Techniques[C]//National Software Engineering Conference (NSEC).2015.
[14]AUTOSAR P.Explanation of Application Interfaces of the Body and Comfort Domain (V1.2.0 R4.0 Rev 2)[OL].
[15]AUTOSAR Partnership.AUTOSAR_MOD_AISpecification[OL].
[1] JIANG Yang-yang, SONG Li-hua, XING Chang-you, ZHANG Guo-min, ZENG Qing-wei. Belief Driven Attack and Defense Policy Optimization Mechanism in Honeypot Game [J]. Computer Science, 2022, 49(9): 333-339.
[2] YUAN Wei-lin, LUO Jun-ren, LU Li-na, CHEN Jia-xing, ZHANG Wan-peng, CHEN Jing. Methods in Adversarial Intelligent Game:A Holistic Comparative Analysis from Perspective of Game Theory and Reinforcement Learning [J]. Computer Science, 2022, 49(8): 191-204.
[3] XU Hao, CAO Gui-jun, YAN Lu, LI Ke, WANG Zhen-hong. Wireless Resource Allocation Algorithm with High Reliability and Low Delay for Railway Container [J]. Computer Science, 2022, 49(6): 39-43.
[4] LI Shao-hui, ZHANG Guo-min, SONG Li-hua, WANG Xiu-lei. Incomplete Information Game Theoretic Analysis to Defend Fingerprinting [J]. Computer Science, 2021, 48(8): 291-299.
[5] BAO Jun-bo, YAN Guang-hui, LI Jun-cheng. SIR Propagation Model Combing Incomplete Information Game [J]. Computer Science, 2020, 47(6): 230-235.
[6] ZHAI Yong, LIU Jin, LIU Lei, CHEN Jie. Analysis of Private Cloud Resource Allocation Management Based on Game Theory in Spatial Data Center [J]. Computer Science, 2020, 47(11A): 373-379.
[7] LI Fang-wei, ZHOU Jia-wei, ZHANG Hai-bo. Anti-eavesdropping Physical Layer Transmission Scheme Based on Time-reversal in D2D Communication Link [J]. Computer Science, 2019, 46(5): 100-104.
[8] ZENG Jin-song, RAO Yun-bo. Intelligent Classification of Massive Information Based on Conflict Game Algorithm [J]. Computer Science, 2018, 45(8): 208-212.
[9] ZHANG Pan-pan, PENG Chang-gen, HAO Chen-yan. Privacy Protection Model and Privacy Metric Methods Based on Privacy Preference [J]. Computer Science, 2018, 45(6): 130-134.
[10] YANG Fan, ZHANG Xiao-song and MING Yong. Research on Resource Allocation Based on Noncooperation Game for OFDMA-WLAN System [J]. Computer Science, 2016, 43(Z6): 319-321.
[11] LIU Mei-lin, WANG Yong, LI Kai, LIU Peng-fei, REN Xing-tian and YANG Jian-hong. Task Scheduling Strategy in Cloud Computing Based on Sequential Game [J]. Computer Science, 2015, 42(Z6): 341-344.
[12] HU Xi,WANG Xin and ZHANG Bin. Stability-oriented Adaptive Routing Overhead Control Algorithm in MANETs [J]. Computer Science, 2014, 41(3): 100-104.
[13] SHI Yun-fang,WU Dong-ying,LIU Sheng-li and GAO Xiang. Research on DDoS Attack-defense Game Model Based on Q-learning [J]. Computer Science, 2014, 41(11): 203-207.
[14] LI Dong,JIANG Jun-li and TANG Xiao-jia. Analysis of Cooperative Game in Repeated Prisoners’ Dilemma Based on Reputation Mechanisms [J]. Computer Science, 2013, 40(4): 240-243.
[15] . Non-cooperative Gaming and Bidding Model Based Resource Allocation in Virtual Machine Environment [J]. Computer Science, 2012, 39(Z6): 380-382.
Full text



No Suggested Reading articles found!