Experimental Evaluation of the Layered Flow-Based Autonomous TSCH Scheduler

Abstract

The Industrial Internet of Things (IIoT) requires wireless connectivity that meets the strict industrial requirements on metrics such as reliability and latency. Promising approaches include Time Slotted Channel Hopping (TSCH) media access, where nodes operate according to a schedule. Autonomously built schedules typically rely on shared resources, where reliability and latency may suffer depending on traffic scenarios and topologies. We have earlier proposed the Layered scheduler, which belongs to a new category of autonomous schedulers: Flow-based scheduling. Layered allocates resources to traffic flows, and as opposed to typical autonomous schedulers, dedicated resources are guaranteed to be scheduled at every hop from source to destination in a convergecast scenario. In addition, Layered minimizes the number of channels required through the novel employment of autonomous spatial reuse. We extend earlier theoretical analysis and simulations by evaluating Layered using the FIT IoT-LAB testbed and compare it to Orchestra and 6TiSCH Minimal scheduler. The experiments demonstrate the feasibility of spatial reuse and that Layered retains performance independent of network topology and traffic intensity - a desirable feature in industrial scenarios. The performance comes at the expense of energy consumption, which in the worst case is 75 % higher compared to Orchestra and Minimal. We also present lessons learned, such as the impact of TSCH configuration on RPL convergence, the benefits of black-listing on performance, and how co-located TSCH networks could be divided by channel offsets as opposed to physical channels. Lastly, we discuss flow-based scheduling in general, its properties, and future research areas.