Abstract: In recent years,the growth of massive data poses severe challenges to existing storage systems,including storage cost and data reliability requirements.Because erasure code can provide higher data reliability under the same storage overhead,it has been paid wide attention.However,the coding characteristics of erasure code increases the extra overhead for the storage system using erasure code,in the process of data repair,such as computing,scheduling,transmission,disk reading and writing,and so on.In recent years,the study of erasure code data recovery is based on the assumption that each node in the distributed storage system is indiscriminate.In a large scale of data center,however,equipment replacement,hardware failure and other reasons may not only cause data loss,but also lead to different sto-rage cost of each storage node in the data center,so that the amount of data stored on each storage node is not always the same,this phenomenon is called storage capacity isomerism.The repair process under the heterogeneous storage capacity is faced with the selection of the providers.It is necessary to design a node selection strategy to make the repair cost lower,and improve the reliability and availability of the storage system.Based on the different transformation cost of nodes participating in repair in the actual repair process of data,this paper proposed a node selection strategy,namely tree topology repair algorithm,to reduce the cost of repair in the whole repair process.The simulation results show that the proposed tree selection strategy can further reduce the cost of data repair compared with the fixed node selection strategy of IFR code

Key words: Data repair, Distributed storage system, Node heterogeneity, Regenerating code