The growth of data volume and the popularity of mobile devices have spawned a large number of low-latency, high-computing applications. At the same time, under the wave of global new energy, the energy efficiency utilization of electronic equipment has also received more and more attention. Due to a large delay and occupying the large bandwidth of cloud computing, and the limited computing power of end devices, mobile edge computing is considered to be the best way to achieve low latency of complex tasks. Wifi routers can provide high bandwidth and can work as intermediate nodes for forwarding tasks. In this report, we propose to use dynamic programming based on wifi routers to dynamically schedule computing tasks to edge computing nodes to achieve maximum bandwidth utilization, under the energy consumption constraint of the user. The experiment result shows that the DP method compared the with other three traditional algorithms can get higher bandwidth by using less Energy cost and fewer numbers workers. Besides, we can effectively search for the last phase Table to save much time by using Computation Reusability.