Abstract: Compared with traditional replication technique,erasure coding is another data redundancy mechanism with lower space overhead at the cost of high repair cost.Locally repairable code is a special kind of erasure code with low repair cost,which is widely deployed in big data storage systems.In order to accommodate itself to dynamic workload and varying failure rate of sto-rage media,modern storage systems make better trade off between access performance and reliability for erasure coded data by means of redundancy transitions.A redundancy transition method,which selectively matches and merges stripes of specific layout,decouples data placement and redundancy transition,is proposed.Furthermore,it reduces the cross-rack network traffic by designing cost quantification and optimization model.In contrast to those algorithms that designing data placement,the proposed algorithm has almost the same performance but eliminates the constraints on data layout and can be run iteratively.Experiment results show that under the two common transition setups,compared with naive approach of random layout,the proposed algorithm approximates the theoretical optimum,mitigates network traffic by 27.74% and 27.47%,and shortens transition time by 39.10% and 22.32% respectively.

Key words: Locally repairable codes, Redundancy transition, Fault-tolerant storage technique, Network traffic optimization, Distributed storage system