In order to achieve the storage QoS and power saving, we proposed a fast data migration/transmission scheme and a power saving algorithm for Dataenode management. The fast data migration/ transmission scheme consists of three mechanisms. First, it uses multicast to improve the network bandwidth and solve the I/O and bandwidth bottlenecks. Then, a network coding is used to increase the network throughput and retain high fault tolerance. Third, it uses a user/Dataenode connection management to prevent missing the important message and collocates with CPU & I/O bound scheduling to make data evenly stored in the system. Experimental results show the proposed fast data migration/transmission improves 56% and 85% efficiency in the upload bandwidth and the response time. The proposed power saving algorithm applies the Kalman filter first and then add with the pattern analysis to predict the system workload to adjust the number of Dataenodes dynamically in order to save power. Experimental results show that the proposed power saving algorithm for Dataenode management achieves more than 92.97% accuracy in the workload prediction and improves 52.25% in power consumption with 3.82% error rate.