The rising adoption of wireless technologies in the In- dustrial Internet of Things has stressed the need for traffic schedulability validation at system design-time to support safety and time critical streams (e.g., process control and emergency response). In this context, the demand-based schedulability tests have recently been proposed in the literature. This work revisits two well-established techniques borrowed from the multi-processor scheduling theory, namely the demand-bound-function (DBF) and the forced-forward-demand-bound-function (FFDBF), and evaluates their performances when adapted to the field of wireless sensor-actuator networks. Simulation experiments when varying network configurations confirm the equal or better accuracy of FFDBF over DBF to estimate both network demand and schedulability. In future work, we aim at building upon these promising results in order to design novel admission control and adaptation strategies that improve network schedulability under varying workload conditions.