Querying Data Services in an Uncertain Environment: A Possibilistic-Based Approach

Omri, Asma; Benouaret, Karim; Omri, Mohamed Nazih; Benslimane, Djamal

doi:10.1109/sitis.2016.47

Cited by 1 publication

(3 citation statements)

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“…Our approach is characterized by hypertext links and to implement them on a browser, we have developed a probabilistic programming language and an analyzer for the validation phase. The results of the experiments show the effectiveness of this new language that we have proposed and thus constitutes an important contribution compared to the existing literature [18,23,21,9,20]. Through this last module, we have proposed new headers for the HTTP protocol making it possible to signal, to users, the uncertainty of resources and, at the same time, determine the degree of uncertainty associated with each of these resources.…”

Section: Discussionmentioning

confidence: 87%

“…On the other hand, De Vettor et al [22] develops a mathematical model to interpret these resources in an uncertain environment by integrating the concept of uncertain representational state transfer (REST)ful resource concept. Other approaches developed by Omri et al [23] and then Omri et al [15], based on possibilistic calculation, tried to solve the problem of interrogating cloud services with possibilities for taking data into account. Two types of invocation have been proposed by these scholars: a conventional invocation and a possibilistic invocation in addition to a new algebra to solve the problem of composition.…”

Section: Related Work: Uncertainty Issues On the Webmentioning

confidence: 99%

“…Does not represent a model based on hypertext navigation. Omri et al [23] Omri et al [15] Provided a flexible cloud service composition framework that can improve service composition results by exploiting data uncertainty.…”

Section: Malki Et Al [21]mentioning

confidence: 99%

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Information Management under uncertain large-scale cloud environment

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“Uncertainty” is related to working with inaccurate data, imprecise and incomplete information, and unreliable results that can lead to irrational decisions. Several approaches to managing uncertain data on the web have been proposed in the literature to resolve this problem. These approaches have failed to find the solution to this problem with accuracy and performance. Our study aims to propose a new probabilistic approach to manage web information resources in an uncertain large-scale cloud environment. Our approach is based on three main steps: (1) modeling uncertain web resources, (2) computing HTTP request model, and (3) interpretation and evaluation of uncertain web resources in a context of classic hypertext navigation. The experimental study shows that the analysis of the execution time necessary for the composition of the services, by our approach, is negligible, compared to that of the other studied approaches. The algorithm which deals with the impact of the variation in the number of nodes, which we have proposed, has also been evaluated and checks all the possibilities in polynomial time and can adapt to many possibilities of multiplexing of values.

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