# An Improved Routing Approach for Enhancing QoS Performance for D2D Communication in B5G Networks
## 2 Related Works
The EDGR improves energy efficiency, network lifetime, and end-to-end delay, compared to other existing geographical routing approaches, in a heterogeneous network scenario. The authors in [31] presented a path-aware geographic perimeter stateless routing (PA-GPSR) to improve wireless networks' performance. The proposed scheme uses node information from a neighbor's table for an optimal path selection and avoids neighbors that discover local maximum on its route for each destination. Moreover, it mitigates the chance of link failure among the nodes owing to node movement in the network. Compared to existing routing schemes, the PA-GPSR scheme improves packet delivery ratio, end-to-end delay, and network yield. In [32], an energy-efficient routing protocol was examined to select control nodes with network functionality for multi-tasking software-defined wireless sensor networks. The proposed algorithm selects the control nodes while considering the nodes' remaining energy and transmission distance with the NP-hard problem. An efficient non-linear weight particle swarm optimization algorithm is employed to maintain a cluster structure. It decreases the data transmission range and improves the network's energy efficiency for handling the NP-hard problem. The simulation results demonstrate that the presented algorithm prolongs the network's lifetime in comparison to other algorithms under various scenarios. In [33], the authors found the least common multiple based routing (LCMR) to balance the traffic load among multiple routes for wireless networks. The proposed routing scheme distributes the data packets on the paths with consideration of the routing time. The data packet distributed mechanism balances the load among the path by minimizing the overall routing time for data packet transmission. The best selected path among the multiple paths is based on the number of hops between the source-destination node pairs. Meanwhile, a multipath OLSR version 2 (MP-OLSRv2) was introduced to discover the multiple disjoint routes in dynamic and high-loaded wireless networks. It utilizes the topological network information with the multipath Dijkstra's algorithm to discover multiple disjoint paths between the source and destination nodes. The MP-OLSRv2 avoids the disjoint paths in which a single-link breakage occurs, and data packets are transmitted in parallel to increase the network's throughput. On the other hand, Ref. [34], presented a hybrid multipath energy consumption and QoS-aware OLSRv2 (MEQSA-OLSRv2) scheme to maintain the tradeoff between the energy consumption and quality of service (QoS) performance of wireless networks. The MEQSA-OLSRv2 utilizes the node rank mechanism according to the multiple-criteria (energy consumption and QoS) value nodes for the selection of an optimal route. Moreover, a link cost assessment function is used to forward the data packets over the multiple disjoint paths during the multipath route selection mechanism. An energy-efficient MPR selection metric is exploited to minimize the flooding of topological messages in the network and extend the MPR's lifetime. Overall, the presented routing scheme is enhanced through the QoS performance network in the MANET-WSN convergence scenario of the IoT network. Based on the literature reviewed so far, it can be seen that there is no study combining multiple device metrics into a single metric for an optimal path selection mechanism. Most research has focused only on two or three device metrics for route selection mechanism. To the best of the authors' knowledge, no research has been reported that combines all of the metric parameters (mobility, battery, link quality status, and contention window size of devices) into an individual route computational metric in D2D communication over IoT-based 5G networks. This paper aims to combine all of the parameter metrics into a single metric for an optimal selection mechanism by employing the MCDM technique to assess network performance.