In order to improve the data processing capabilities of network edge and meet the requirements of large bandwidth and low latency of the terminal, a cloud computing platform based on edge infrastructure is built, and an optical fiber network model is designed with dynamic bandwidth adjustment. A timing optimization algorithm based on edge cloud computing is proposed and applied to optical fiber wireless networks. The average transmission delay of the timing optimization algorithm is simulated and analyzed through OPNET software, and the results show that the maximum delay after optimization is 43.1 ms, which is only 34.2% of the traditional method. The experiment analyzes the data communication between multiple terminals in the local area network. The transmission efficiency, optical fiber channel utilization and transmission energy consumption of the three algorithms have been discussed. The experimental results show that the test results using the timing optimization algorithm have been significantly improved. Its transmission efficiency has increased by nearly double, the channel utilization rate of edge cloud data average transmission delay has increased by about 6.2%, and the network transmission energy consumption has the best value. The optical fiber wireless network model and its optimization algorithm have significant improvements in transmission delay, channel utilization, and network energy consumption. It has certain advantages in improving the selection of optical fiber communication links and data interaction at the edge.