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Wide-area transfer of large data sets is still a big challenge despite the deployment of high-bandwidth networks with speeds reaching 100 Gbps. Most users fail to obtain even a fraction of theoretical speeds promised by these networks. Effective usage of the available network capacity has become increasingly important for wide-area data movement. We have developed a "data transfer scheduling and optimization system as a Cloud-hosted service", StorkCloud, which will mitigate the large-scale end-to-end data movement bottleneck by efficiently utilizing underlying networks and effectively scheduling and optimizing data transfers. In this paper, we present the initial design and prototype implementation of StorkCloud, and show its effectiveness in large dataset transfers across geographically distant storage sites, data centers, and collaborating institutions.