Nowadays, underwater acoustic sensor networks (UASN) facilitate communication between sensors using the acoustic signals to monitor underwater environments, including oceans, rivers, and seas. However, UASNs have limited bandwidth with high latency and consume large amount of energy. To overcome these issues, a network topology optimization technique is proposed for reducing the energy consumption of networking. The distributed network architecture (DNA) network model is utilized for acoustic sensor networks (ASN), which allows the adaptive and dynamic topology optimization. DNA allows terminals to act as AP, by optimizing resource allocation and reducing costs. By resource allocating, the dynamic tracking of the optimum topology by genetic algorithm provides the optimal network configuration for the present traffic conditions. Finally, the proposed optimization is done through the acoustic sensor networks topology optimization (ANTO) which optimizes the model by reducing the energy consumption, minimizes the latency, and gives efficient data communication. The proposed model gained better results in terms of energy consumption of 65, 78, 54, 15, and 60 with the nodes of 50, 100, 150, 200, and 200 when compared with the existing method clustering-based dragonfly optimization (CDFO) respectively.