## 2 Related Work
The simulation results demonstrate that the LMNR as the multipath routing can significantly improve robustness in wireless networked control systems. However, any performances in term of the control perspective are not evaluated in the reference [3]. Reference [27] studies routing and control approaches for reducing wireless error-prone effects in WSANs for a mobile robot squad. The objective of this system is to measure and control desired locations of all moving robots. In the control perspective, parameter tuning of a proportional integral derivative (PID) controller and process estimation by a Kalman filter are employed to manage the results of the unreliable wireless communication. To reduce packet loss, multipath routing protocols are evaluated and compared with the AODV in IEEE 802.15.4 wireless networks. An integration of control errors over time is used for the control performance evaluation. We note that the control error is the difference between the actual sensing level and the predefined control target of the physical system. For this case, the actual sensing level and the predefined control target are the actual location and the desired robot location, respectively. The wireless network performance is represented by average end-to-end delay, percentages of packet delivery and routing overhead of the entire simulation time. Reference [27] concludes that the multipath routing is worse than the AODV in mobile WSAN environments. This summary extends the finding from the previous work in [3] where the multipath routing can increase the packet delivery at a sink in stationary WSANs. However, the energy consumption of sensor nodes as a major issue in WSAN [1,2] is not studied in both references [3] and [27]. Reference [4] compares the performance of centralized and distributed control schemes for a building temperature control application over WSANs by the simulation study. The simulation platform is developed using the integration of OMNeT\(++\) tool and MATLAB. A wireless network is simulated by OMNeT\(++\), while control decision making is carried in MATLAB. The network protocols employ the geographical and energy aware routing and the IEEE 802.15.4 protocols. Control errors as the difference between the predefined control target and the measured room temperature are recorded, and the average of the packet loss for the whole simulation is computed for the performance evaluation. However, the major objective of the work in [4] is to develop an appropriate control scheme for WSANs. An exploration of how routing mechanisms affect the desirable control target is beyond the scope of the study. In [28], an efficient delay-based load-aware on-demand routing (D-LAOR) protocol for mobile _ad-hoc_ networks is presented. D-LAOR determines the optimal path by utilizing both the total route delay and the hop-count as the route selection criterion. D-LAOR attempts to avoid any routes with high loads for delivering sensing data by selecting the route with the lowest total delay and the shortest hop-count. Thus, load balancing is achieved by this strategy. However, In the D-LAOR mechanism, each node updates its route entry only when both the total delay and the hop-count from the newly acquired route are smaller than the previous one. By this approach, the shortest route with the smallest total delay may contain a larger load than a route with longer hop-count, as confirmed in Section 5. Having a high load can exhaust a node's resource and increase the possibility of packet loss. Furthermore, the research methodology of the work in [28] is not developed for WSANs. Any control functions are not considered. Accordingly, how D-LAOR can be applied for control applications is not guaranteed. In [32], the simulation study of the greenhouse climate control system over IEEE 802.15.4 WSANs is introduced. To control the temperature and the humidity inside the greenhouse for the crop growth by using an event-based control approach is the main aim of the study.