# MBMQA: A Multicriteria-Aware Routing Approach for the IoT 5G Network Based on D2D Communication
## 2 Related Works
Moreover, it was proven that the proposed algorithm achieves better performance than the other distributed algorithms in terms of average delay, maximum delay, and fairness. In addition, the authors in [40,41] presented and investigated key recent advances of network slicing toward enabling several Internet of Things smart applications. A taxonomy was devised for network slicing using different parameters: key design principles, enablers, slicing resources levels, service function chaining schemes, physical infrastructures, and security. Subsequently, in [42], the authors proposed a proactive approach and cluster formation mechanism to utilize the decision-making process in wireless networks with D2D cooperation to optimize network reliability. The authors suggested a heuristic approach that combines with linear optimization problem formulation to provide high efficiency for high-density device networks, such as IoT and WSN networks. The proposed approach improves network reliability and prolongs the network lifetime. Their work manipulates the Multipath-Optimized Link State Routing Protocol version 2 (MP-OLSRv2) [43], presented by [PERSON] et al., which is a hybrid multi-path routing protocol. The MP-OLSRv2 balances the load among multiple paths in order to discover destinations and forward the data to their respective forwarding relay. It is categorized as a reactive routing protocol and does not retain the record of every destination; nevertheless, it randomly selects a path as requested by a device in the network. Though it is not guaranteed that the same path will always route to the same destination, route entries are held in reserve for a short duration of time; then they expire due to changes in the network's configurations. MP-OLSRv2 efficiently selects multiple devices and forms multiple paths to the destinations. The devices selected along the path(s) are termed Multi-Point Relay (MPR). The MPR is utilized to broadcast topological alterations in the network to spread updated information regarding the device's position across the network. The MP-OLSRv2 routing protocol does not consider the energy information of the devices; therefore, the low-energy devices will be turned off once all of their residual energy is consumed. This could occur, since there is an excellent chance that the same device could be selected as an MPR to reach a certain destination, which would drain the battery. In [44], the authors introduced hybrid multi-path energy and quality of service (QoS)-aware optimized link-state routing protocol version 2 (MEQSA-OLSRv2) to provide a tradeoff between energy efficiency and QoS in IoT networks. For optimal path selection between source and destination devices, their work utilized device rank metrics according to multiple criteria (energy and QoS) to evaluate link quality during multiple path computation. Flooding of the topological information is reduced by selecting the highly energy efficient MPR sets of the devices in the network. The MEQSA-OLSRv2 significantly enhanced the network QoS in the heavy traffic load and high-mobility scenario networks by transmitting data packets over multiple disjointed paths based on link quality assessment. Thus far, all the studies reviewed above have considered a single metric factor, such as mobility, energy consumption or queue length size of the device, for route computerization. However, based on the literature, as per our knowledge, none of the research combines all three parameters in a single route computational metric in an IoT 5G network based on D2D communication. Therefore, this paper combines the mobility, energy consumption, and queue length size parameter into a single route selection metric with the back-pressure algorithm to investigate the network performance.