With demands growing at exponential rates, these networks are struggling to cope with large data volumes, real-time responses, and overall network performance. Wide area networking infrastructures (WANs), particularly science and research WANs, are the backbone for moving large volumes of scientific data between experimental facilities and data centers. ![]() Additionally, a fine-tuning file system can improve remote write performance in DTNs with a long-distance network. We found that NVMe-TCP is more suitable for remote data read than remote data write over the networks, and using RAID0 can significantly improve performance in a long-distance network. This study evaluates NVMe-over-TCP (NVMe-TCP) in a long-distance network using different file systems and configurations to characterize remote NVMe file system access performance in MAN and WAN data moving scenarios. As recent storage system development uses modern fabrics to provide faster remote data access with lower overhead, traditional data movement using Data Transfer Nodes must cope with the paradigm shift from a store-and-forward model to streaming data with direct storage access over the networks. However, the fundamental concept of copying data from one machine to another has not been challenged in collaborative science. Furthermore, we extend the SCinet DTN-as-a-Service framework to incorporate new techniques, solve optimization issues in data-intensive science and evaluate NVMe over Fabrics with multiple WAN testbeds to examine its performance and discover new opportunities for optimization.Äistributing Big Data for science is pushing the capabilities of networks and computing systems. To support increasing demands for the large volume of science data movement during Supercomputing (SC) conferences, we proposed a SCinet DTN-as-a-Service framework orchestrating the desired optimization to meet users, applications, and providers’ requirements. However, recent NVMe over Fabrics studies have been limited to local storage fabrics. New solutions for such data movement require new paradigms and technologies, such as NVMe over Fabrics, which provides high-performance data movement with direct remote NVMe device access over traditional fabrics. ![]() Supporting transfers of science big data over Wide Area Networks (WANs) with Data Transfer Nodes (DTNs) requires optimizing multiple parameters within the underlying infrastructure.
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