The major contributions of this paper are summarized as follows: . We investigate a new automotive architecture and implementation method. We propose an extended SAE (Society of Automotive Engineer) Benchmark and the use of DDS middleware as an alternative for the existing architecture. . We detail the implementation of the electronic stability unit based on the extended SAE benchmark. . We propose a new design of the DDS based on the MBD approach. Thus, the implementation of the application and the new DDS block are realized under SIMULINK. We intend to improve DDS's programming approach, facilitate con¯guring and generation of DDS description and take into account the real-time network drivers. . In order to validate our DDS implementation and highlight its contributions in the context of hard real-time automotive systems, we detail latency computation for automotive networks, and we present the implemented algorithm to calculate the Worst Case Response Time (WCRT). We prove that DDS qualities of service on the top of the SAE vehicle application are respected. We also give a comparison of system performance using real time networks FlexRay and Ethernet.

本文的主要贡献总结如下：
1. 我们研究了一种新的汽车架构和实现方法。我们提出了扩展的SAE（汽车工程师协会）基准以及将DDS中间件作为现有架构的替代方案。
2. 我们详细介绍了基于扩展SAE基准的电子稳定单元的实现。
3. 我们提出了基于MBD方法的DDS的新设计。因此，应用程序的实现和新的DDS块在SIMULINK下完成。我们旨在改进DDS的编程方法，简化DDS描述的配置和生成，并考虑实时网络驱动程序。
4. 为了验证我们的DDS实现并突出其在硬实时汽车系统环境中的贡献，我们详细说明了汽车网络的延迟计算，并介绍了计算最坏情况响应时间（WCRT）的实现算法。我们证明了DDS在SAE车辆应用程序之上的服务质量得到了满足。我们还通过使用实时网络FlexRay和以太网对系统性能进行了比较。

相关问题

In the proposed algorithm, the access prices of BSs are adjusted according to incomes and load situations in the leaderlevel game, and each UE independently chooses the BS that maximizes its payoff (or minimizes its payment) in the follower-level game. Thus, the algorithm achieves optimization in a distributed manner. When a small BS is overloaded, the price will increase to ensure that the offloaded UE has a higher access payment. For the design of the price, a particle swarm optimization-based pricing strategy (PSO-PS) is proposed to maximize the BS revenue. Finally, we use the resident-oriented Gale-Shapley (GS) algorithm to obtain a stable single-BS association. The main contributions of this paper can be summarized as follows:翻译

在所提出的算法中，基站的接入价格根据领导者层次博弈中的收入和负载情况进行调整，而每个UE在追随者层次博弈中独立选择使其效益最大化（或支付最小化）的基站。因此，该算法以分布式的方式实现了优化。当小型基站超载时，价格将增加，以确保离载的UE具有更高的接入支付。在价格设计方面，提出了一种基于粒子群优化（PSO-PS）的定价策略，以最大化基站的收入。最后，我们使用面向居民的Gale-Shapley（GS）算法来获得稳定的单基站关联。本文的主要贡献可以总结如下：

Topic: The influence of parents, teachers, and classmates on one's life Parents, teachers, and classmates are the most influential people in one's life. They shape our thoughts, beliefs, and actions, and help us become who we are today. Parents are the first teachers of a child. They teach us the values of life, discipline, and ethics. They provide us with emotional support and guide us through the ups and downs of life. They instill in us the confidence to face challenges and the determination to succeed. Teachers play a crucial role in shaping our intellect and career. They impart knowledge and skills that help us achieve our goals. They inspire us to learn and explore new horizons. They guide us towards the right path and help us develop our potential. Classmates are our peers who share our experiences and challenges. They provide us with a sense of belonging and help us develop our social skills. They teach us the value of cooperation, teamwork, and friendship. They help us grow and learn from our mistakes. In conclusion, parents, teachers, and classmates are the pillars of our lives. Their influence shapes our personality, character, and future. We should be grateful for their contributions and strive to learn from them.翻译

父母、老师和同学是一个人生活中最具影响力的人。他们塑造了我们的思想、信仰和行动，帮助我们成为今天的自己。父母是孩子的第一位老师。他们教导我们生活的价值观、纪律和道德。他们提供我们情感上的支持，指导我们度过生活中的高低起伏。他们在我们内心灌输了面对挑战的信心和成功的决心。老师在塑造我们的智力和职业生涯方面起着至关重要的作用。他们传授知识和技能，帮助我们实现自己的目标。他们激励我们学习和探索新的领域。他们指引我们走向正确的道路，帮助我们发挥我们的潜力。同学是我们共同经历和面对挑战的同龄人。他们给我们一种归属感，帮助我们发展社交技能。他们教我们合作、团队合作和友谊的价值。他们帮助我们成长，并从错误中吸取教训。总之，父母、老师和同学是我们生活的支柱。他们的影响塑造了我们的个性、品格和未来。我们应该感激他们的贡献，并努力从他们身上学习。