Section: Software

DIET

Participants : Daniel Balouek, Eddy Caron [correspondant] , Frédéric Desprez, Maurice Djibril Faye, Cristian Klein, Arnaud Lefray, Guillaume Mercier, Adrian Muresan, Jonathan Rouzaud-Cornabas, Lamiel Toch, Huaxi Zhang.

Huge problems can now be processed over the Internet thanks to Grid and Cloud middleware systems. The use of on-the-shelf applications is needed by scientists of other disciplines. Moreover, the computational power and memory needs of such applications may of course not be met by every workstation. Thus, the RPC paradigm seems to be a good candidate to build Problem Solving Environments on the Grid or Cloud. The aim of the Diet project (http://graal.ens-lyon.fr/DIET ) is to develop a set of tools to build computational servers accessible through a GridRPC API.

Moreover, the aim of a middleware system such as Diet is to provide a transparent access to a pool of computational servers. Diet focuses on offering such a service at a very large scale. A client which has a problem to solve should be able to obtain a reference to the server that is best suited for it. Diet is designed to take into account the data location when scheduling jobs. Data are kept as long as possible on (or near to) the computational servers in order to minimize transfer times. This kind of optimization is mandatory when performing job scheduling on a wide-area network. Diet is built upon Server Daemons. The scheduler is scattered across a hierarchy of Local Agents and Master Agents. Applications targeted for the Diet platform are now able to exert a degree of control over the scheduling subsystem via plug-in schedulers. As the applications that are to be deployed on the Grid vary greatly in terms of performance demands, the Diet plug-in scheduler facility permits the application designer to express application needs and features in order that they be taken into account when application tasks are scheduled. These features are invoked at runtime after a user has submitted a service request to the MA, which broadcasts the request to its agent hierarchy.

In 2012, our objective was to extend Diet to benefit from virtualized resources such as ones coming from cloud platforms. Wa have designed how it can be extended to access virtualized resources. We can easily support new cloud service providers and cloud middleware systems. We have prototyped the new version of Diet which benefits from virtualized resources. As cloud resources are dynamic, we have on-going research in the field of automatic and elastic deployment for middleware systems. Diet will be able to extend and reduce the amount on aggregated resources and adjust itself when resources fail. We have started works to extend our data management software, Dagda , to take advantage of cloud storage and the new data computing paradigms. Moreover we have upgraded the workflow engine of Diet to take advantage of cloud resources. Diet Cloud will be able to provide a large scale distributed and secured platform that spans on a pool of federated resources that range from dedicated HPC clusters and grid to public and private clouds.

In the context of the Seed4C project, we have studied how secured our platform, authenticated and secured interactions between the different parts of our middleware and between our middleware and its users. We have worked to show how to securely use public cloud storage without taking the risk of losing confidentiality of data stored on them.