Hybrid Genetic-Based Traffic Scheduling Algorithm in In-Vehicle Time Sensitive Networks

Demand for smart driving in cars spurs development of time-sensitive networks in vehicles. Traffic scheduling mechanism is the core mechanism of time-sensitive networks, which realize latency and bandwidth requirements for different types of traffic flows by scheduling the order and time of data fra...

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Bibliographic Details
Published in2023 3rd International Conference on Frontiers of Electronics, Information and Computation Technologies (ICFEICT) pp. 388 - 394
Main Authors Zhu, Xiaosong, Gong, Bei, Zhu, Haotian
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2023
Subjects
component
Genetic Algorithms
Genetics
In-Vehicle Time Sensitive Networks
Perturbation methods
Schedules
Scheduling algorithms
Search problems
Sociology
Telecommunication traffic
Traffic Scheduling
Variable Neighborhood Search
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Summary:Demand for smart driving in cars spurs development of time-sensitive networks in vehicles. Traffic scheduling mechanism is the core mechanism of time-sensitive networks, which realize latency and bandwidth requirements for different types of traffic flows by scheduling the order and time of data frames in the network. To address the problems of poor performance and easy to fall into local optimal solutions of existing genetic traffic scheduling algorithms, we propose an algorithm combining variable neighborhood search and population perturbation in genetic algorithm, which takes the queuing delay generated during traffic scheduling as an adaptive function, and improves the adaptation of individuals through iteration of population to obtain the optimal data frame transmission for traffic scheduling The optimal data frame transmission order for traffic scheduling is obtained by iterating the population to improve individual adaptation. The algorithm is demonstrated to have better performance through simulation comparison experiments.
DOI:10.1109/ICFEICT59519.2023.00071