Abstract
Erasure Coding is a advanced redundancy technique to ensure data reliability of the distributed storage system(DSS). However, when data is first written into DSS, it may be hesitantly to choose the specific parameters of erasure coding to balance the repair cost and storage utilization. In this paper, we design and implement VDRR-EC, a new distributed storage framework which exploit deep q network (DQN) mind to automatically decide the parameters of erasure coding to optimize traditional distributed storage system performance. Experimental results in real cluster environment show that VDRR-EC reduces data repair frequency and storage cost by 10.7%~19.2% and approximately 3.5% respectively, the penalty is acceptable additional network transport overhead and computing overhead.
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