Abstract
With billions of connected devices in the near future, the major challenge is to develop networks to build an Industrial Internet of Things which is scalable, energy-efficient, reliable and affordable. To this end, low-power wireless personal area networks (LP-WPAN) provide a solution at minimum costs. However, to ensure continuous performance verification, LP-WPAN requires a centrally monitored and controlled service. This work proposes such an edge service, i.e. network monitoring and optimal reconfiguration of scheduled LP-WPANs. The approach is based on a transformation of the schedule into a new model, interference graphs. The interference graphs allow to design evaluation and rescheduling recommender methods to monitor and reconfigure the schedule. An experimental setup was developed to test and validate the approach. The results show that the model and methods provide an accurate representation of the behavior of the network, and that the new rescheduling recommender greatly improves the network’s performance, compared to random rescheduling.