## 4 Fuzzy Logic-Based Routing Algorithms  
This section reviews the-state-of-the-art routing algorithms that use fuzzy logic systems for selecting the next forwarding nodes among candidate sensor nodes. This section highlights the main parameters utilized by each algorithm with different fuzzy logic systems. All of the presented algorithms focus on forwarding strategies by selecting the node that is placed closer to the sink node. In fact, the improper selection of the next forwarding node can be considered as one of the main problems in routing protocols that have a direct impact on packets' delivery. The selection of the next forwarding nodes with high residual energy, best link quality, and physical distance helps in reducing packet loss, leading to increase reliability, energy-efficiency, and reducing delay. Furthermore, proper selection to the next hop reduces interference and can achieve better load balancing between the intermediate nodes in terms of energy consumption and network traffic flows, which is depicted in Figure 5. As shown in Figure 5a, if both nodes 1 and 2 want to send data to node 8, then node one may choose the blue route, and node two may choose the green route which will operand nodes 4 and 6, as they are relaying the traffic and are thus consuming more energy and reducing their batteries. On the other hand, in Figure 5b, node 1 has chosen a different route, which loads balance the traffic among all nodes, thus not overloading any nodes and obtaining a fair energy consumption among all nodes. To solve these problems, several researchers have introduced several fuzzy-based intelligent delays and energy-aware algorithms. In what follows, a survey of the most known examples is presented. [PERSON] and [PERSON] [43] proposed a protocol that comprises a fuzzy-based energy-aware routing mechanism (FEARM) and fuzzy logic system. The protocol starts by finding the next forwarding nodes among neighbors by combining four parameters as input values for the FLS, namely, link quality, residual energy, physical distance, and available buffer, as shown in Figure 6. The output of FLS can be considered as a metric value named \"chance of becoming the next node\". In terms of routing, this \begin{table}
\begin{tabular}{c c c} \hline \hline
**Fuzzy-Based Clustering Algorithms** & **Fuzzy Descriptors** & **Average Lifetime in Rounds** \\ \hline CHEF [31] & remaining energy of a node, local distance & 630 \\ FL-EEC/D [33] & energy, BS\_Distance, AVG\_Energy, & 1437 \\  & density, compact & \\  & CH energy, & \\ Energy aware cluster and neuro fuzzy & distance (CH, BS) & \\ based routing algorithm, FBCFP [34] & distance (CH, node) & 1400 \\  & CH degree & \\ Fuzzy logic for clustering scheme [35] & densities, distances, residual & 675 \\ Fuzzy logic-based clustering & battery power, mobility, centrality & 300 \\  & self-management model [37] & residual energy, radio energy dissipation, & 500 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Half of the nodes dies (HND) comparison. Figure 5: Depicts the routing paths for the traffic generated by nodes 1 and 2, in green and blue colors, respectively. (**a**) Demonstration of a possibility for overloading nodes 4 and 6 while routing the traffic to node 8, where (**b**) shows a more balanced traffic distribution among the nodes. protocol takes advantage of [PERSON]'s algorithm to establish a different route and then discovers the best path. Simulation results show that the proposed protocol reduces packet loss, delay, and energy consumption. Moreover, it proves that the use of fuzzy with four parameters performs better results than fuzzy with fewer parameters. [PERSON] et al. [44] proposed a novel fuzzy logic-based geographical routing (FLGR) protocol to enhance routing overhead, void, and location accuracy problems. FLGR proposes a novel-forwarding mode based on the fuzzy location region of the receiver node and void avoidance scheme, being a fuzzy logic system that is capable of choosing the routes with a lower number of hops and with high packet delivery ratio.