학술논문

Hybrid Scheduling of Tasks and Messages for TSN-Based Avionics Systems
Document Type
Periodical
Source
IEEE Transactions on Industrial Informatics IEEE Trans. Ind. Inf. Industrial Informatics, IEEE Transactions on. 20(2):1081-1092 Feb, 2024
Subject
Power, Energy and Industry Applications
Signal Processing and Analysis
Computing and Processing
Communication, Networking and Broadcast Technologies
Task analysis
Delays
Aerospace electronics
Job shop scheduling
Optimization
Logic gates
Informatics
Avionics system
time-sensitive networking (TSN)
hybrid scheduling
task chain
determinism
function delay
Language
ISSN
1551-3203
1941-0050
Abstract
Time-sensitive networking (TSN) has been considered as a promising networking candidate for avionics systems due to its capability of deterministic communication. In such TSN-based avionics systems, the network scheduling enables the timely transmission of messages. However, this is insufficient to satisfy the real-time requirements of functions since functions involve the chain execution of several tasks where messages only serve for the inter-task communication. In order to enhance the functionality of TSN-based avionics systems, scheduling should be extended from the network level to the system level to coordinate message transmission with task execution. Then, how to efficiently implement the hybrid scheduling of tasks and messages becomes an important issue. In this article, we construct a novel hybrid scheduling framework for TSN-based avionics systems, which consists of system consistency constraints, in-loop function delay calculation, and two hybrid scheduling algorithms. Consistency constraints restrict the unexpected interaction of messages and tasks for hybrid scheduling to guarantee the system-level determinism. Function delay is the end-to-end delay of the task chain, and its calculation provides the optimization objective for hybrid scheduling indicated by two metrics. Scheduling algorithms improve solving efficiency and functional performance through the incremental strategies of message dynamic ordering and task-message rescheduling. Experimental results verify that, compared with existing scheduling work that considers the dependency of messages on tasks, our work can complete complex scheduling for large systems even with hundreds of functions and can reduce function delays by 69% in reaction delay and 37% in age delay.