Scheduling Optimization of Time-Triggered Cyber-Physical Systems Based on Fuzzy-Controlled QPSO and SMT Solver

Jie Jian, Lide Wang, Huang Chen and Xiaobo Nie
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Jie Jian: School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
Lide Wang: School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
Huang Chen: School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
Xiaobo Nie: School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China

Energies, 2020, vol. 13, issue 3, 1-22

Abstract: The time-triggered communication paradigm is a cost-efficient way to meet the real-time requirements of cyber-physical systems. It is a non-deterministic polynomial NP-complete problem for multi-hop networks and non-strictly periodic traffic. A two-level scheduling approach is proposed to simplify the complexity during optimization. In the first level, a fuzzy-controlled quantum-behaved particle swarm optimization (FQPSO) algorithm is proposed to optimize the scheduling performance by assigning time-triggered frame instances to the basic periods of each link. In order to prevent population from high aggregation, a random mutation mechanism is used to disturb particles at the aggregation point and enhance the diversity at later stages. Fuzzy logic is introduced and well designed to realize a dynamic adaptive adjustment of the contraction–expansion coefficient and mutation rate in FQPSO. In the second level, we use an improved Satisfiability Modulo Theories (SMT) scheduling algorithm to solve the collision-free and temporal constraints. A schedulability ranking method is proposed to accelerate the computation of the SMT-based incremental scheduler. Our approach can co-optimize the jitter and load balance of communication for an off-line schedule. The experiments show that the proposed approach can improve the performance of the scheduling table, reduce the optimization time, and reserve space for incremental messages.

Keywords: real-time systems; communication networks; Ethernet networks; particle swarm optimization; scheduling algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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