## 2 Related Work
This means that if a single route fails or is unavailable, a new route must be discovered, which requires more time and increases the delay or failure rate of data delivery. Among the protocols for WSNs/IoT that evaluate other metrics apart from the number of hops, LABILE (The implementation of the LABILE protocol is available for downloading at [[http://www.gercom.ufpa.br/downloads/wsn/](http://www.gercom.ufpa.br/downloads/wsn/)]([http://www.gercom.ufpa.br/downloads/wsn/](http://www.gercom.ufpa.br/downloads/wsn/))) (Link Quality-Based Lexical Routing) [24] can be pointed out. LABILE proposes a routing algorithm based on lexical structures and link quality evaluation. Through the use of LQI, _i.e._, a metric provided by the physical layer of IEEE 802.15.4 standard [25], LABILE is able to evaluate the link quality. The LABILE proposal evaluates end-to-end link quality, by classifying the possible values of LQI into good or bad. In specific terms, it determines a threshold value for link classification, where the lowest values of LQI (below the threshold) are considered bad, and represent links that are more susceptible to packet loss. During the route discovery process, all the bad links are counted, recorded and reported with the aid of an additional field in RREQ and RREP messages, which is called _WeakLinks_. The purpose of LABILE is to select routes with good link qualities. However, this behavior implies that these routes have an exhaustive use, and lead to the premature death of these nodes. This is due to a lack of mechanisms for determining when there is a need to use alternative routes. Thus, LABILE does not take account energy-efficiency into account during the route selection process and load balancing mechanisms as expected for multipath WSN/IoT scenarios. The EEURP (Energy Efficient Unicast Routing Protocol) [26] proposes a cost function to select routes based on hop count, the average energy consumption in the end-to-end path, and the minimum energy level. EEURP also uses additional fields for RREQ and RREP messages, which report the total amount of residual energy of a path and the lowest energy level along a route. The minimum energy of a path shows if there is a hop with a critical level of energy. The route discovery mechanism takes into account that only the destination node answers the RREQ messages, _i.e._, the intermediate nodes that have an available route to the destination do not reply by using a RREP message. This approach is required to calculate the energy level of the entire route, although it creates an extra signaling overhead, leading to an additional expenditure of energy and congestion in the WSNs. The main drawback of EEURP is the fact that it does not include a mechanism to estimate the link quality level. EEURP is focused only on the network lifetime and does not consider QoS support for IoT applications. Despite being specified for WSNs, EEURP was evaluated with the aid of the IEEE 802.11 radios, which have a higher transmission power and more bandwidth than typical radios used for WSNs/IoT applications. A routing and reliable transmission scheme for IoT applications based on percolation theory and small-world concept was proposed in [27]. In the routing process, nodes broadcast probe messages to discover available routes and select them based on a small-world strategy. The proposed routing scheme is able to operate with multiple paths, but it does not provide load balancing techniques to provide a fair and efficient usage of resources in multipath scenarios as expected for IoT applications (and avoid the hot-spot problem). Mechanisms for link evaluation and residual energy are also not included in the route selection. A routing protocol based on three possible routing techniques is presented in [22]. The routing schemes are the following: simple routing, based on Round-Robin, and weighted-Round Robin. In simple routing models, each network node selects a single node to route all packets to each round.