Abstract
This paper considers the problem of how to reduce the I/O overhead of data update operations in erasure coding based storage systems. To this end, we first analyze the I/O overhead of update operations with current update approaches. We find the key to reduce such I/O overhead is designing a scheduling algorithm to construct the sequence of update operations. Such an algorithm needs to execute with a time limit, since update requests work under a stringent latency constraint. To quickly schedule the order of update operations, we propose an efficient algorithm, namely UCODR. Our theoretical analysis verifies that UCODR can effectively reduce the I/O overhead of update operations when multiple blocks are updated. To further confirm its effectiveness, we implement a prototype storage system to deploy UCODR with different erasure codes. Extensive experiments are conducted on the prototype storage system with real-world traces. The experimental results show that UCODR can reduce the time of update operations by up to 35 percent and improve the throughput of the storage system by up to 67 percent, compared with the state-of-the-art update approaches.
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