  Time-Triggered Ethernet (TTEthernet) has been widely applied in many
scenarios such as industrial internet, automotive electronics, and aerospace,
where offline routing and scheduling for TTEthernet has been largely
investigated. However, predetermined routes and schedules cannot meet the
demands in some agile scenarios, such as smart factories, autonomous driving,
and satellite network switching, where the transmission requests join in and
leave the network frequently. Thus, we study the online joint routing and
scheduling problem for TTEthernet. However, balancing efficient and effective
routing and scheduling in an online environment can be quite challenging. To
ensure high-quality and fast routing and scheduling, we first design a
time-slot expanded graph (TSEG) to model the available resources of TTEthernet
over time. The fine-grained representation of TSEG allows us to select a time
slot via selecting an edge, thus transforming the scheduling problem into a
simple routing problem. Next, we design a dynamic weighting method for each
edge in TSEG and further propose an algorithm to co-optimize the routing and
scheduling. Our scheme enhances the TTEthernet throughput by co-optimizing the
routing and scheduling to eliminate potential conflicts among flow requests, as
compared to existing methods. The extensive simulation results show that our
scheme runs >400 times faster than standard solutions (i.e., ILP solver), while
the gap is only 2% to the optimally scheduled number of flow requests. Besides,
as compared to existing schemes, our method can improve the successfully
scheduled number of flows by more than 18%.
