FlexRay is a vehicular communication protocol designed to meet growing requirements in hard real time automotive systems and to support time triggered as well as event triggered paradigms. Thus, there has been a lot o...FlexRay is a vehicular communication protocol designed to meet growing requirements in hard real time automotive systems and to support time triggered as well as event triggered paradigms. Thus, there has been a lot of recent interest in timing analysis techniques in order to provide bounds for the message communication times on FlexRay. In this paper, we present an approach to compute the WCRT （worst case response time） for periodic and sporadic tasks, within a FlexRay node, responsible for sending messages on the FlexRay SS （static segment） and DS （dynamic segment）. On the other hand, we propose a scheduling table for messages transmitted over the FlexRay SS. An interesting innovation would be the use of a scheduling algorithm performed on a FlexRay node to guarantee the arrival of the right data on the right time and to ensure that every task meets its deadline. As application, we will use the extended SAE （society of automotive engineers） benchmark for the FlexRay network to identify the static and dynamic tasks, and calculate the response time, based on a hybrid scheduling model to further prove that the deadline of the SAE benchmark applications is insured.展开更多
文摘FlexRay is a vehicular communication protocol designed to meet growing requirements in hard real time automotive systems and to support time triggered as well as event triggered paradigms. Thus, there has been a lot of recent interest in timing analysis techniques in order to provide bounds for the message communication times on FlexRay. In this paper, we present an approach to compute the WCRT （worst case response time） for periodic and sporadic tasks, within a FlexRay node, responsible for sending messages on the FlexRay SS （static segment） and DS （dynamic segment）. On the other hand, we propose a scheduling table for messages transmitted over the FlexRay SS. An interesting innovation would be the use of a scheduling algorithm performed on a FlexRay node to guarantee the arrival of the right data on the right time and to ensure that every task meets its deadline. As application, we will use the extended SAE （society of automotive engineers） benchmark for the FlexRay network to identify the static and dynamic tasks, and calculate the response time, based on a hybrid scheduling model to further prove that the deadline of the SAE benchmark applications is insured.
