Survey of Uncertainty Handling in Cloud Service Discovery and Composition

TL;DR

This survey reviews various approaches to handling uncertainty in cloud service discovery and composition, emphasizing risk modeling to improve reliability and meet user requirements in cloud environments.

Contribution

It categorizes existing methods based on risk modeling, providing a comprehensive overview of uncertainty handling in cloud service discovery and composition.

Findings

Various risk modeling techniques are used in existing approaches.

Uncertainty handling improves reliability in cloud service composition.

The survey identifies gaps and future directions in the field.

Abstract

With the spread of services related to cloud environment, it is tiresome and time consuming for users to look for the appropriate service that meet with their needs. Therefore, finding a valid and reliable service is essential. However, in case a single cloud service cannot fulfil every user requirements, a composition of cloud services is needed. In addition, the need to treat uncertainty in cloud service discovery and composition induces a lot of concerns in order to minimize the risk. Risk includes some sort of either loss or damage which is possible to be received by a target (i.e., the environment, cloud providers or customers). In this paper, we will focus on the uncertainty application for cloud service discovery and composition. A set of existing approaches in literature are reviewed and categorized according to the risk modeling.