LAUSR

Abstract Storage density of the traditional cloud storage system is not big and the comprehensive storage efficiency is low. When the large amount of data increases dramatically, the storage efficiency of the system would be decreased seriously. Therefore, with the development of cloud storage technology, an application of Markov Decision Process in Scheduling Strategy on cloud storage (MDPSS) is proposed in this paper. MDPSS can predict periodically in stages by using the steady Markov decision process and select the optimal storage node easily. By scheduling the data to the optimal node in real time, MDPSS can enhance the flexibility of the data storage and reduce the storage cost. Simulation results show that MDPSS has the ability to predict accurately when the size of the data is different.