# Routing Protocols for Low Power and Lossy Networks in Internet of Things Applications
## 4 Enhanced Routing Solutions for Internet of Things Networks
### RPL Objective Functions
EAOF seeks to increase the network lifetime and reliability of Biomedical Wireless Sensor Networks (BWSN). According to the authors, a BWSN should be able to work without human intervention for an extended period to further require reliable levels of QoS and efficient energy consumption. Thus, EAOF uses ETX and Remaining Energy (RE) to compute the best path to the root node aiming to satisfy the requirements of BWSN. EAOF performs the best parent selection in three steps and using two configurable parameters: MAX_ETX and MIN_ENER. In the first step, the proposed OF uses MAX_ETX as a threshold to define the maximum value that a potential parent should have to be considered in the next step. Thus, a node only can be considered as a candidate to be the best parent if it has an ETX value to the sink lower than MAX_ETX. In the next step, EAOF compares the rank of the candidate with the rank of the node. In the last step, the node with the highest RE is selected. EAOF introduces some hysteresis through the MIN_ENER parameter. Hence, a potential node only should be selected as the new preferred parent if the difference between its RE and the RE of the current parent is higher than MIN_ENER. This way, EAOF seeks to select the preferred parent with lower ETX and higher RE. Some approaches do not propose a completely new OF, but improve how the rank of the nodes is computed, introducing a new routing metric. In [97], the authors proposed an additive composite metric called the Lifetime and Latency Aggregatable Metric (L\({}^{2}\)AM). L\({}^{2}\)AM aims to provide balanced energy consumption considering the reliability of data transmission along the path. To this end, the proposed routing metric merges a link reliability metric (i.e., ETX) with a new energy consumption metric termed Fully Simplified Exponential Lifetime Cost (FSELC). FSELC represents the power cost that each node needs to pay to send a message. During the RPL functioning, the nodes use DIO messages both for transporting information about the metrics and for informing the L\({}^{2}\)AM value computed for each neighbor. The L\({}^{2}\)AM value must be summed along the path to obtain the overall route cost. When a node needs to send a packet to the root, it should select the path with the lowest summation of L\({}^{2}\)AM. Thus, the proposed metric allows the node to use routes that are reliable and energy efficient. A fuzzy-based OF was presented in [74; 98]. The proposed OF-FL (Objective Function Fuzzy Logic) aims to create a robust OF that can fulfill different routing requirements through consideration of several network metrics. In the work, the authors highlighted that only one, or a simple combination of, routing metrics cannot be sufficient to create a reliable path between a sender and a receiver. Thus, OF-FL uses a fuzzy system to combine four primary routing metrics (end-to-end delay, hop count, link quality, and node energy) and obtain a value that indicates the quality of a neighbor. As any OF, the information used to compute the rank of nodes piggybacks onto DIO messages. Hence, the nodes that receive a DIO execute the fuzzy system for computing the rank of the message sender neighbor. After, looking for the set of neighbors and its respective qualities, the OF-FL selects the best preferred parent based on the application requirements. Thus, OF-FL permits RPL, considering different network aspects during the route construction phase. Another fuzzy-based OF was introduced in [99]. The proposal sought to merge different routing metrics to optimize QoS and energy consumption. The FUZZYOF combines three routing metrics, which are the delay, ETX, and energy, to obtain a fourth value termed quality that represents the path cost. Delay is the average time it takes for a packet to reach its destination. ETX, as already introduced, is the expected number of transmissions for a message to be delivered successfully. The energy metric expresses the lowest energy level among the nodes that compose a path.