Distributed wireless networks provide scalable and decentralized connectivity for applications ranging from IoT and vehicular communication to emergency response. However, unlocking their full potential requires overcoming persistent challenges, including inefficient routing strategies, energy limitations, and interference management. Traditional routing metrics—primarily based on hop count or heuristic combinations—fail to optimize throughput, energy efficiency, and reliability, particularly as network size increases. To address these limitations, we systematically analyze the multi-layer networking problem and derive optimized routing metrics that simultaneously maximize total network throughput, minimize energy consumption, enhance path reliability, and enable effective load balancing. Our proposed metrics—centered on link length square, inverse channel gain, and link utilization—are rigorously evaluated through extensive simulations. Results demonstrate substantial performance gains over traditional hop-count-based approaches, with improvements of several-fold in end-to-end throughput and up to 20 dB in power efficiency. These metrics consistently deliver high capacity, low latency, and robust operation in realistic large-scale urban scenarios—historically a major obstacle for ad hoc networks. These findings pave the way for practical, sustainable deployment of large-scale distributed wireless networks.