## 1 Introduction
### Related Works
The MP-OLSRv2 exploits the multi-path Dijkstra's shortest path algorithm to explore multiple disjoint routes from a source to a destination device based on the network topological information. The proposed approach avoids the disjoint routes if a single link failure occurred and transmits the data packets in a parallel manner to aggregate network throughput. The MP-OLSRv2 approach enhances the overall network throughput and data delivery reliability in a dynamic and high-loaded network by avoiding link failure relay devices in the optimal route. Whereas, in the article [41], the authors proposed hybrid multi-path energy and QoS based on OLSRv2 (MEQSA-OLSRv2) routing approach in IoT networks to maintain energy consumption and QoS performance. The device rank metric concept is utilized for the selection of the best route based on a multicriteria (energy and QoS) value to estimate the link cost assessment function during the multi-path route computation. The proposed approach forwards the data packets to the multiple disjoint routes according to the link cost assessment function. The energy-efficient multipoint relays (MPRs) selection mechanism is employed to mitigate the topological flooding packets in the network and prolong the MPRs' lifetime. Consequently, the MEQSA-OLSRv2 routing approach is able to boost the QoS performance metric even in a heavy traffic load and high-mobility network scenarios. Based on the literature, up to the present moment, most of the research has only focused on the combination of two- or three-parameter metrics of the intermediate devices (two or three combinations of metrics, i.e., mobility, energy consumption, link quality, or device queue length size) for route computation. As per the author's best knowledge, there are no such studies that merge all the parameter metrics in one single route computation for IoT 5G network based on D2D communications. Thus, this paper integrates all the parameter metrics in one single metric for the route computation process with the Backpressure algorithm to evaluate the network QoS performances. The energy, mobility, queue length, and link quality-aware routing (EMBLR) approach utilized the functionalities of the well-known existing routing approaches and modified with the combination of device parameter metrics, i.e., mobility, energy consumption, link quality, and queue length size of the devices for the route selection procedure. Besides, the multicriteria decision making (MCDM) decision mechanism is employed for the selection of the best route among the multiple routes. The conceptual structure, framework, implementation feature, and methodology adopted for the proposed EMBLR routing approach is depicted in Figure 3. The framework elaborates on the structural elements of the proposed EMBLR routing approach and their incorporation to accomplish the research objective. The routing protocols in wireless networks are highly dependent on the established communication channel links. Adjusting the resource allocation within the network can change the channel capacity of an individual link that influences the routing of data packets and alters the overall network performance. The proposed framework utilizes the link quality among the users with the Backpressure algorithm in order to schedules the routing of data packets and allocates the efficient resources to the users which improve network QoS performances. The findings presented in the study can be potentially used in the optimization formulations for various wireless communication technologies and useful for designing the efficient routing approach in the next-generation wireless communication networks. Moreover, the proposed EMBLR routing scheme provides high network QoS performance even in heavy traffic load and high-mobility scenarios. The following section describes the system model of the proposed EMBLR routing approach for D2D communication over the IoT 5G network.