In modern science, the growing complexity of large-scale scientific projects has led to an increasing reliance on cross-facility scientific workflows, where resources and expertise from multiple institutions and geographic locations are leveraged to accelerate scientific discovery. These workflows often require transmitting huge amounts of scientific data through wide-area networks. Although high-speed networks like ESnet and transfer services such as Globus have improved data mobility, several challenges remain. The sheer volume of data can overwhelm network bandwidth, widely used transport protocols such as TCP suffer from inefficiencies due to retransmissions triggered by packet loss, and existing fault-tolerance mechanisms like erasure coding introduce substantial overhead.

Erasure coding (EC) plays a crucial role in the fault tolerance of modern distributed storage systems (DSS). Inspired by recent research on storage configuration, we study the configuration sensitivity of EC in real DSS in this paper. We systematically inject faults to trigger EC recovery under various configurations, and measure the impact on recovery time and storage overhead quantitatively. Our results show that configurations may affect the EC recovery time significantly (e.g., up to 426%). More interestingly, theoretically superior codes may perform worse in DSS under certain configurations. Also, there is a system checking period before EC recovery that accounts for 41% to 58% of the overall system recovery time, which has been largely ignored in previous studies. Finally, in terms of storage overhead, EC may introduce 32.3% to 72.0% more write amplification (WA) than the theoretical expectation, and we derive a formula to help estimate WA more precisely. Our work suggests the importance of considering the context of real DSS for EC research, and we hope the methodology and findings can contribute to a firmer footing for EC optimization in practice.