## 2 Related Work
In the greenhouse control system, sensors gather the temperature and the humidity inside the greenhouse. These collected data are sent to the controller via wireless communications. The controller with the PI control algorithm makes decision and commands the actuators (_i.e._, a ventilator and a heater) to operate their actions. Due to the use of the event-based control approach, each sensor will transmit its sensing data if the value of the difference between the current value of the measured signal and the previous value is greater than a limit threshold. Therefore, an actuator output is only produced when a change is found in the system. The simulation results demonstrate that the event-based control approach can reduce the number of data transmission and can prolong the actuator lifetime. However, the routing mechanism and the energy consumption of a node which can affect the control output are not studied in the reference [32]. Reference [33] develops a decentralized control algorithm for lighting control applications in WSANs. For the proposed decentralized control method, sensor nodes that detect the presence of people in a building first initiate the estimated control signals. The control signal for this case indicates the brightness of lights. After the collaboration among sensors for exchanging the estimated control signals, each node can determine the optimal control signal for controlling the brightness of lights. By this approach, the lights are controlled depending on the response of the occupancy sensors. The occupied areas must be bright and the unoccupied areas should be dark. The experimental results from implemented Note testbed reveal that the decentralized control algorithm gives the better control performance than the centralized control algorithm. However, the routing algorithm including its effect to resulting control outputs and the energy consumption issue are not investigated in the reference [33]. Reference [34] presents a flexible time-triggered sampling scheme for wireless networked control systems. To adjust the sampling periods of sensors by considering the workload variations is the main goal of the study. The authors claim that the control system may become unstable due to the effects of packet loss and delay in the overloaded conditions. On the other hand, the system performance may be worse than possible due to low resource utilization in the under-loaded conditions. In order to deal with this issue, the actuator in this work will inform the sensor to determine the new sampling period if it does not receive the control commands within a specific deadline time. The simulation results show that the flexible time-triggered sampling scheme can cope with workload variation and can improve the resource efficiency of the system. However, the designing of network protocols for wireless networked control systems are out of the scope of this reference as mentioned by the authors. In [2], a design methodology for WSANs in mobile control applications is presented. The objective of the study is to develop a simple efficient method on actuators for dealing with unpredictable packet loss caused by unreliable link quality in mobile WSANs. For this purpose, the actuator will perform its actions based on the previous control command values when a sensing data is lost. The actuator calculates an estimate of control command by applying the PID algorithm. We note that the link quality of WSANs in terms of the packet loss rate is extracted from the real experiments; the authors use this packet loss rate information for the simulation study. The simulation results demonstrate that the proposed solution can deal with packet loss; the control performances in terms of the control system output and the integral of absolute error (IAE) are significantly improved. However, how routing algorithms affect the control system response is not studied in the reference [2].