Towards Design Support for Provenance Awareness: A Classification of Provenance Questions

As the complexity of online services increases, there is a corresponding need for service-oriented systems to provide support for answering questions about how they have processed and produced data. This need is particularly evident in compositions of services, where audits of each individual service’s use do not provide a connected picture of the composition’s processing history. The provenance awareness of a system is its ability to answer questions about the history of its processing, through recording provenance data during execution. As the size and usage of a system increases, so can the size of the provenance data recorded, leading to increased demands on storage and decreased performance of the service. However, the exact impact of provenance recording depends on what details of the service execution are being documented. Our goal is to make provenance awareness accessible as an explicit non-functional property (NFP) in composite service specifications, as is common for performance or reliability properties. This would enable composite service designers to analyse the properties of their services to see whether they meet users ’ requirements based on the provenance questions they could ask about the service’s outputs and the dependent performance, storage and other properties. We present a preliminary approach towards this end, focusing on the step of categorising potential provenance questions according to their effect on other NFPs, so that the provenance awareness of a service can be specified as the categories of questions it can answer

Coût dans le Cloud: rationalisation et d'essais de recherche

International audienceCloud Computing provides simplicity to its consumers by saving them the efforts to deal with their own infrastructure, environments or software. This simplicity relies on the shifting of problems from the client to the provider, introducing new paradigms (virtualization, scalability, flexibility, pay-per-use, etc.). This simplicity comes with a price for the consumer that may accurately, or not, reflect the costs of the provider. In this paper we propose to identify the different points, in the Cloud Computing architecture, where the costs are generated , how their reduction/optimisation are considered, and finally we point-out which of these key points need to be further investigated, according to their foreseeable efficiency.Cloud Computing fournit la simplicité à ses consommateurs en leur permettant d'économiser les efforts pour faire face à leurs propres infrastructures, d'environnements ou logiciel. Cette simplicité repose sur le déplacement des problèmes du client au fournisseur, l'introduction de nouveaux paradigmes (virtualisation, l'évolutivité, la flexibilité, pay-per-use, etc.). Cette simplicité est livré avec un prix pour le consommateur qui peut précision, ou non, refléter les coûts du fournisseur. Dans cet article, nous vous proposons d'identifier les différents points, dans l'architecture Cloud Computing, où les coûts sont générés, comment leur réduction / optimisation sont considérés, et, enfin, nous soulignons-savoir lequel de ces points clés doivent encore être étudiées, selon leur rendement prévisible