## 6 CMR-WSN Mobility Management Utilizing Fuzzy Logic
The evaluation results clearly show that the adaptive fuzzy logic mobility controller outperformed the non-adaptive fuzzy logic controller in terms of all evaluation metrics (packet loss, power consumption, and on-time triggering). Table 6 depicts the latest proposed solutions to support mobility in wireless sensor networks. The table summarizes the objectives of each protocol, the metrics used as input to the fuzzy logic controller, and, finally, the evaluation environment. The two out of four protocols were evaluated in a real industrial environments [57; 63] and under harsh conditions, which makes them applicable for unpredictable CMRS environments. The FLMC [57] had the least overhead among all the fuzzy-based mobility management solutions and used only two metrics (RSSI, link loss) that were locally available to all nodes. Processing only two available metrics will help with the design of an optimal controller that can optimize the performance of the system. There are many challenges for cooperative multi-robotic wireless sensor network systems, especially when the mobility of the robots is considered. The mobility management solutions provided should be intelligent enough to improve the overall performance of the system. Therefore, any proposed mobility protocol should provide controlled performance considering the following main characteristics of mobile robots:  
Figure 16: Fuzzy logic-based mobility controller [57]. Figure 15: Relationship between RSSI, link loss, and end-to-end loss [57]. 1 High number of mobile robot systems with embedded wireless sensors. * Dynamic topology. * Limited resources (e.g., power, computation). All of these characteristics must be addressed in order to achieve a controlled system that supports an efficient and effective communication protocol between mobile robots. In addition, on the basis of the evaluation presented in the aforementioned papers, we can only compare the results from three of them [57; 63; 69] in terms of packet losses, number of handoffs, and power consumption. Due to the different evaluation parameters and testbed field, it is not possible to directly compare the solutions; therefore, we decided to compare the performance of the proposed solutions with the RSSI-based solution. Figure 17 shows the comparison of ireless controller area network (Wireless CAN) [63], FLMC [57], and adaptive-FLMC [69] in terms of packet losses. It is obvious that all the proposed solutions decrease the packet losses compared to the RSSI-based solution. More specifically, Wireless CAN reduces packet loss by 73.8%, FLMC by 69.8%, and adaptive-FLMC by 74.7%. Furthermore, Figure 18 shows the number of handoffs per solution. Again, there is a comparison with the RSSI-based solution. This type of comparison shows how each solution effectively avoids the ping-pong effect. Based on the evaluation, Wireless CAN reduced the number of handoffs by 54.8%, FMLC by 87%, and, finally, adaptive-FLMC by 92.6%. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Protocol** & **Objectives** & **Fuzzy Logic Metrics** & **Evaluation Environment** \\ \hline FLMC [57] & Triggering the handoff & RSSI, link loss & Real industrial environment (refinery), simulation Cooja [71] \\  & & Expected number of & \\ MoMoRo [62] & Extra layer to enable & transmissions (ETX), received & Indoor and outdoor \\  & mobility of the nodes & signal strength (RSS), and & \\  & & symbol error rate (SER) variance & \\ Wireless CAN [63] & Triggering the handoff & Moving state, channel condition, & Real industrial environment \\ Mobility management & & and packet delivery & \\ incorporating fuzzy logic & Predict the node’s & Remaining energy & Simulation (NS3) \\ for a heterogeneous IP & mobility and energy & mobility & \\ environment [66] & & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: A summary of fuzzy logic-based WSN mobility management protocols. Figure 17: Packet loss comparison. Finally, Table 7 depicts the percentage of power reduction of each proposed solution with an RSSI-based solution.