Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
On Satisfying Timing Constraints in Hard-Real-Time Systems
IEEE Transactions on Software Engineering
Performance Evaluation
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Message scheduling is a critical research issue in the Controller Area Network (CAN). Messages that fail to meet predefined deadlines may deteriorate system performance significantly. In this paper, we propose an online Message-Scheduling Controller (MSC), which is realised by the Radial Basis Function (RBF) network. The MSC exploits two novel learning algorithms to adaptively tune its internal parameters. The learning algorithms provide complementary effects to prevent possible causes of non-uniform bandwidth allocation among requesting messages and to reduce possibilities of Transmission Failures (TFs). Simulation results show that the proposed algorithm outperforms the existing scheduling methods.