Towards an understanding of cloud services under uncertainty: A possibilistic approach

Abstract

With the development of Web technologies and the increasing use of the Internet, more and more web services are being deployed. This gave birth to what called cloud services, which are widely used for building distributed cloud applications. With cloud-based service delivery, it seems hard for users to find the right service for their needs. However, if a single cloud service cannot meet all user requirements, a cloud service composition is required. With the rise of Web services on the Internet, the quality of response has been considered as an important criterion to choose the most relevant answer. The performance of web services may vary depending on the dynamic Internet environment, which makes the quality of service uncertain. Then, the need to deal with uncertainty in the operation of cloud services. Over the past decade, several approaches to service composition have been proposed to cope with this challenge. In this article, we provide a flexible and efficient cloud services composition framework that can respond to user queries and improve cloud services composition results by exploiting data uncertainty. We then introduce an effective strategy that allows modeling, invocation, and composition of services by dealing with data uncertainty. The experimental evaluation of a real case study demonstrates the effectiveness of our proposed strategy.