Data Migration for Large Scientific Datasets in Clouds

1Institute for Computer Science and Control, Hungarian Academy of Sciences (MTA SZTAKI), Budapest, Hungary, akos.hajnal@sztaki.mta.hu, eniko.nagy@sztaki.mta.hu, peter.kacsuk@sztaki.mta.hu *Correspondence: Peter Kacsuk, nstitute for Computer Science and Control, Hungarian Academy of Sciences (MTA SZTAKI), Budapest, Hungary, peter.kacsuk@ sztaki.mta.hu Abstract Transferring large data files between various storages including cloud storages is an important task both for academic and commercial users. This should be done in an efficient and secure way. The paper describes Data Avenue that fulfills all these conditions. Data Avenue can efficiently transfer large files even in the range of TerraBytes among storages having very different access protocols (Amazon S3, OpenStack Swift, SFTP, SRM, iRODS, etc.). It can be used in personal, organizational and public deployment with all the security mechanisms required for these usage configurations. Data Avenue can be used by a GUI as well as by a REST API. The papers describes in detail all these features and usage modes of Data Avenue and also provides performance measurement results proving the efficiency of the tool that can be accessed and used via several public web pages.