Modélisation sémantique du cloud computing : vers une composition de services DaaS à sémantique incertaine

Abdelhamid Malki 1, 2
2 SOC - Service Oriented Computing
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : With the emergence of the Open Data movement, hundreds of thousands of datasets from various concerns (e.g., healthcare, governmental, statistic, etc.) are now freely available on Internet. A good portion of these datasets are accessed and queried through Cloud DaaS services to benefit from the flexibility, the interoperability and the scalability that the SOA and Cloud Computing paradigms bring to data integration. In this context, user’s queries often require the composition of multiple Cloud DaaS services to be answered. Defining the semantics of DaaS services is the first step towards automating their composition. An interesting approach to define the semantics of DaaS services is by describing them as semantic views over a domain ontology. However, defining such semantic views cannot always be done with certainty, especially when the service’s returned data are too complex. In this dissertation, we propose a probabilistic approach to model the semantic uncertainty of data services. In our approach, a DaaS service with an uncertain semantics is described by several possible semantic views, each one is associated with a probability. Services along with their possible semantic views are represented in probabilistic service registry (PSR).According to the services dependencies, the correlations in PSR can be represented by two different models :Block-Independent-Disjoint model (noted BID), and directed probabilistic graphical model (Bayesian network). Based on our modeling, we study the problem of interpreting an existing composition involving services with uncertain semantics. We also study the problem of compositing uncertain DaaS services to answer a user query, and propose efficient methods to compute the different possible compositions and their probabilities. We conduct a series of experiments to evaluate the performance of our composition algorithms. The obtained results show the efficiency and the scalability of our proposed solutions
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Abdelhamid Malki. Modélisation sémantique du cloud computing : vers une composition de services DaaS à sémantique incertaine. Autre [cs.OH]. Université Claude Bernard - Lyon I; Université Djillali Liabès (Sidi Bel-Abbès, Algérie), 2015. Français. ⟨NNT : 2015LYO10050⟩. ⟨tel-01152568⟩

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