Significant obstacles to 5G installations include the ongoing expansion and proliferation of Internet of Things (IoT) devices as well as the rising demand for fast and dependable communication. The paper puts forth an efficient and novel bioinspired method using Gray Wolf Optimization (GWO) and Ant Lion Optimization (ALO) to improve device-to-device (D2D) communications in the IoT to address these issues for real-time scenarios. This work is necessary because 5G communication networks must minimize D2D communication delay, increase throughput, improve energy efficiency, and guarantee a higher packet delivery ratio (PDR). As a result of their inability to accomplish several goals at once, current optimization techniques frequently perform less than optimally and have trouble assuring uninterrupted IoT communications. In order to solve two essential features of IoT D2D communications, the suggested model leverages the combined advantages of GWO and ALO to overcome the shortcomings of previous approaches. First, GWO is used to identify Line of Sight (LOS) paths between various IoT devices, allowing for faster and more effective connection, considerably enhancing the speed of all communications. Second, ALO is used to regulate packet rates, optimize throughput, and keep energy levels within reasonable bounds, hence improving energy efficiency and packet delivery ratios. The proposed dual bioinspired model has many benefits. The model reduces D2D communication delay by a stunning 15.5% with the integration of GWO and ALO, ensuring quicker and more responsive communications between IoT devices. Furthermore, it improves energy efficiency by 8.3%, extending the battery life of IoT devices and lowering overall energy consumption. Additionally, the concept improves throughput by a significant 12.4%, allowing for faster data transfer rates and more simultaneous connections. Last but not least, the suggested model guarantees a 2.9% increase in PDR, suggesting a more stable and dependable communication framework that results in fewer data losses and improved network performance levels. In conclusion, the research presents a unique QoS-aware methodology to maximize high-speed IoT D2D communications across 5G installations by combining the strengths of GWO and ALO. The experimental results show that the model significantly outperforms recently proposed optimization techniques, making it a promising approach to overcome the difficulties faced by 5G communication networks and promoting future seamless IoT connectivity characteristics for real-time scenarios.