Soumaya Amdouni

Bio: Soumaya Amdouni is an academic researcher. The author has contributed to research in topics: Data Web & Probabilistic database. The author has co-authored 1 publications.

Web services composition in uncertain environments

Abstract: In this thesis we focus on the data web services composition problem and study the impact of the uncertainty that may be associated with the output of a service on the service selection and composition processes. This work is motivated by the increasing number of application domains where data web services may return uncertain data, including the e-commerce, scientific data exploration, open web data, etc. We call such services that return uncertain data as uncertain services. In this dissertation, we propose new models and techniques for the selection and the composition of uncertain data web services. Our techniques are based on well established fuzzy and probabilistic database theories and can handle the uncertainty efficiently. First, we proposed a composition model that takes into account the user preferences. In our model, user preferences are modelled as fuzzy constraints, and services are described with fuzzy constraints to better characterize their accessed data. The composition model features also a composition algebra that allows us to rank the returned results based on their relevance to user's preferences. Second, we proposed a probabilistic approach to model the uncertainty of the data returned by uncertain data services. Specifically, we extended the web service description standards (e.g., WSDL) to represent the outputs' probabilities. We also extended the service invocation process to take into account the uncertainty of input data. This extension is based on the possible worlds theory used in the probabilistic databases. We proposed also a set of probability-aware composition operators that are necessary to orchestrate uncertain data services. Since a composition may accept multiple orchestration plans and not all of them compute the correct probabilities of outputs, we defined a set of conditions to check if a plan is safe (i.e., computes the probabilities correctly) or not. We implemented our different techniques and applied them to the real-estate and e-commerce domains. We provide a performance study of our different composition techniques