The experimental WSAN testbed in this paper only has one route generator and one schedule generator. We can investigate further whether it is better to have multiple route generators and schedule generators. It doesn’t give reason why 2 ms guard time is suitable. Numerical analysis or experiments should be done on the impact of longer or shorter guard time.
For both the fixed priority scheduling and dynamic priority scheduling, we may apply machine learning approach to assign suitable priority. Instead of man-made rules, the machine learning approach can learn from large amounts of data.
There are only simulation results for the 4 optimization methods used in selecting sampling rate. It is much better to also include the performance for real application. It is also desirable to give numerical analysis of the optimization performance and run time of these 4 algorithms. We can also consider using special hardware to speed up the execution.
In the emergency communication section, this paper assumes the control networks consist of regular flows and emergency flows and they have predetermined deadlines. These assumptions are generally true. But if we have signals of various kind of emergency, how we set the threshold to determine whether it is emergent signal. The deadlines may vary and related to other factors beside the signal itself.
There are only one experiment (water tank systems) for the proposed emergency communication protocol. It needs more experiments for various applications to prove the protocol is effective.