The FlexRay bus is a communication standard used in the automotive industry. It offers a deterministic message transmission in the static segment following a time-triggered schedule. Even if its bandwidth is ten times higher than the bandwidth of controller area network (CAN), its throughput limits are going to be reached in high-class car models soon. A solution that could postpone this problem is to use an efficient scheduling algorithm that exploits both channels of the FlexRay. The significant and often neglected feature that can theoretically double the bandwidth is the possibility to use two independent communication channels that can intercommunicate through the gateway. In this paper, we propose a heuristic algorithm that decomposes the scheduling problem to the electronic control unit (ECU)-to-channel assignment subproblem, which decides which channel the ECUs should be connected to and the channel scheduling subproblem that creates static segment communication schedules for both channels. The algorithm is able to create a schedule for cases where channels are configured in the independent mode, as well as in the fault-tolerant mode or in cases where just part of the signals are fault tolerant. Finally, the algorithm is evaluated on real data and synthesized data, and the relation between the portion of fault-tolerant signals and the number of allocated slots is presented.
Lange et al. @cite_20 used the rate monotonic scheduling method for the response time analysis of the static segment. However, this paper requires modifications of the middleware. Bouhouch et al. described an analysis of Data Distribution Service (DDS) for the FlexRay bus based on the subscription-publication paradigm in @cite_12 and Sojka et al. @cite_21 considered flexible reservation mechanisms for distributed real-time applications. The concept of time analysis considering both static and dynamic segment of the FlexRay communication protocol is presented in @cite_2 and @cite_17 .
@cite_21 @cite_2 @cite_20 @cite_12 @cite_17
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In the last decade, the FlexRay communication protocol has been promoted as a standard for dependable in-vehicular communications. In the FlexRay protocol, the communication timeline is organized as a sequence of four segments, whereas the Static Segment assigns a set of static slots for the transmission of synchronous messages. In this paper, we address the following problems: "How to efficiently transmit periodic messages in the Static Segment without requiring their periods to be multiples of, or to be synchronized with the FlexRay Communication Cycle?" "Is it possible to guarantee that periodic messages are transferred before their deadlines, without imposing such strict synchronization?" Unlike traditional approaches that use linear-programming based techniques, we evaluate the minimum number of allocated slots using traditional Response Time Analysis (RTA). The use of RTA techniques allows us to consider the timing requirements associated to each of the asynchronous message streams. Unlike other approaches, the RTA-based technique proposed in this paper: (a) is able to deal with message stream sets where periods are not multiple of the FlexRay cycle duration and (b) does not require the strict synchronization between tasks signals at the application layer and slots at the FlexRay communication controller. The proposed slot allocation scheme may be of high practical interest when considering the interconnection of FlexRay CAN in-vehicular communication systems, allowing the remapping of existing CAN message streams to FlexRay. FlexRay is a communication bus (and associated protocol) that supports transmission of time-triggered and event-triggered frames. A method for determining the worst-case response-time of FlexRay frames is proposed by Pop in 2008, and is formulated as iterative sequence of Integer Linear Programming (ILP) problems. As we show, the method of Pop is conservative (overestimates the response time). We propose a new ILP formulation that computes a precise value of the worst-case response time of FlexRay frames transmitted in the dynamic segment. Furthermore, our approach is non-iterative as it requires the solving of a single ILP for computing, respectively, the delay of full bus cycles and the delay of a partial (last) bus cycle. The proposed solution is also validated by applying it to a SAE benchmark and can be used for formally guaranteeing that no message will miss its deadline during system operation. The proliferation of high-volume time-critical Web services such as online trading calls for a scalable server design that allows meeting individual response-time guarantees of real time transactions. A main challenge is to honor these guarantees despite unpredictability in incoming server load. The extremely high volume of real-time service requests mandates constant-time scheduling and schedulability analysis algorithms (as opposed to polynomial or logarithmic ones in the number of current requests). The paper makes two major contributions towards developing an architecture and theoretical foundations for scalable real-time servers operating in dynamic environments. First, we derive a tight utilization bound for schedulability of aperiodic tasks (requests) that allows implementing a constant time schedulability test on the server. We demonstrate that Liu and Layland's schedulable utilization bound of ln 2 does not apply to aperiodic tasks, and prove that an optimal arrival-time independent scheduling policy will meet all aperiodic task deadlines if utilization is maintained below 1 1+ spl radic (1 2). Second, we show that aperiodic deadline-monotonic scheduling is the optimal arrival-time-independent scheduling policy for aperiodic tasks. This result is used to optimally prioritize server requests. Evaluation of a utilization control loop that maintains server utilization below the bound shows that the approach is effective in meeting all individual deadlines in a high performance real-time server. We consider the problem of resource allocation in downlink OFDMA systems for multi service and unknown environment. Due to users' mobility and intercell interference, the base station cannot predict neither the Signal to Noise Ratio (SNR) of each user in future time slots nor their probability distribution functions. In addition, the traffic is bursty in general with unknown arrival. The probability distribution functions of the SNR, channel state and traffic arrival density are then unknown. Achieving a multi service Quality of Service (QoS) while optimizing the performance of the system (e.g. total throughput) is a hard and interesting task since it depends on the unknown future traffic and SNR values. In this paper we solve this problem by modeling the multiuser queuing system as a discrete time linear dynamic system. We develop a robust H∞ controller to regulate the queues of different users. The queues and Packet Drop Rates (PDR) are controlled by proposing a minimum data rate according to the demanded service type of each user. The data rate vector proposed by the controller is then fed as a constraint to an instantaneous resource allocation framework. This instantaneous problem is formulated as a convex optimization problem for instantaneous subcarrier and power allocation decisions. Simulation results show small delays and better fairness among users.