UNICORE is a European Grid Technology with more than 10 years of history. Originating from the Su... more UNICORE is a European Grid Technology with more than 10 years of history. Originating from the Supercomputing domain, the latest version UNICORE 6 has turned into a general-purpose Grid technology that follows established standards and offers a rich set of features to its users. The paper starts with an architectural insight into UNICORE 6, highlighting the workflow features, standards and the different clients. Next, the current state of advancement is presented by describing recent developments. The paper closes with an outlook on future planned developments.
With the continuous growth of data generated in various scientific and commercial endeavors and t... more With the continuous growth of data generated in various scientific and commercial endeavors and the rising need for interdisciplinary studies and applications in e-Science easy exchange of information and computation resources capable of processing large amounts of data to allow ad-hoc co-operation becomes ever more important. Unfortunately different communities often use incompatible resource management systems. In this work we try to alleviate the difficulties occurring on bridging the gap between different research eco-systems by federating resources and thus unifying resource access. To this end, our solution presented in this paper outlines a secure, simple, yet highly interoperable and flexible architecture using RESTful Web services and WebDAV. While, first and foremost in the Grid computing domain, there are already standards and solutions in place addressing related problems, our solution differs from those approaches by allowing to federate data storage systems that are not aware of being federated. Access to these is enabled by our federation layer using storage system specific connectors. Hence, our federation approach is intended as an abstraction layer on top of existing storage or middleware solutions, allowing for a more uniform access mechanism. Additionally, our solution also allows for submission and management of computational jobs on said data, thereby federating not only data but also computational resources. Once resource access is unified, information from different data formats can be semantically unified by information extraction methods. It is our belief that the work in this paper can complement existing Grid computing efforts by facilitating access to data storage system not inherently available via commonly used Grid computing standards. Full list of author information is available at the end of the article for application steering, user management and the creation of complex workflows, but also of resources for data management . A strong advantage of Grid computing is the ability to maintain distributed and heterogeneous resources using a middleware layer to distribute computational jobs or delegate user access to data storage space. The use of distributed computing resources becomes more and more important in many research fields using state-of-the-art information systems to even enable collaborative work over institutional boundaries. To some extent, Grid and, more recently, Cloud resources can be used for distributing computing tasks or providing access to distributed data resources. Since, generally speaking,
UNICORE is a European Grid Technology with more than 10 years of history. Originating from the Su... more UNICORE is a European Grid Technology with more than 10 years of history. Originating from the Supercomputing domain, the latest version UNICORE 6 has turned into a general-purpose Grid technology that follows established standards and offers a rich set of features to its users. The paper starts with an architectural insight into UNICORE 6, highlighting the workflow features, standards and the different clients. Next, the current state of advancement is presented by describing recent developments. The paper closes with an outlook on future planned developments.
With the continuous growth of data generated in various scientific and commercial endeavors and t... more With the continuous growth of data generated in various scientific and commercial endeavors and the rising need for interdisciplinary studies and applications in e-Science easy exchange of information and computation resources capable of processing large amounts of data to allow ad-hoc co-operation becomes ever more important. Unfortunately different communities often use incompatible resource management systems. In this work we try to alleviate the difficulties occurring on bridging the gap between different research eco-systems by federating resources and thus unifying resource access. To this end, our solution presented in this paper outlines a secure, simple, yet highly interoperable and flexible architecture using RESTful Web services and WebDAV. While, first and foremost in the Grid computing domain, there are already standards and solutions in place addressing related problems, our solution differs from those approaches by allowing to federate data storage systems that are not aware of being federated. Access to these is enabled by our federation layer using storage system specific connectors. Hence, our federation approach is intended as an abstraction layer on top of existing storage or middleware solutions, allowing for a more uniform access mechanism. Additionally, our solution also allows for submission and management of computational jobs on said data, thereby federating not only data but also computational resources. Once resource access is unified, information from different data formats can be semantically unified by information extraction methods. It is our belief that the work in this paper can complement existing Grid computing efforts by facilitating access to data storage system not inherently available via commonly used Grid computing standards. Full list of author information is available at the end of the article for application steering, user management and the creation of complex workflows, but also of resources for data management . A strong advantage of Grid computing is the ability to maintain distributed and heterogeneous resources using a middleware layer to distribute computational jobs or delegate user access to data storage space. The use of distributed computing resources becomes more and more important in many research fields using state-of-the-art information systems to even enable collaborative work over institutional boundaries. To some extent, Grid and, more recently, Cloud resources can be used for distributing computing tasks or providing access to distributed data resources. Since, generally speaking,
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Papers by Jason Daivandy