Ontologies in Cloud Computing—Review and Future Directions

Abstract

Cloud computing as a technology has the capacity to enhance cooperation, scalability, accessibility, and offers discount prospects using improved and effective computing, and this capability helps organizations to stay focused. Ontologies are used to model knowledge. Once knowledge is modeled, knowledge management systems can be used to search, match, visualize knowledge, and also infer new knowledge. Ontologies use semantic analysis to define information within an environment with interconnecting relationships between heterogeneous sets. This paper aims to provide a comprehensive review of the existing literature on ontology in cloud computing and defines the state of the art. We applied the systematic literature review (SLR) approach and identified 400 articles; 58 of the articles were selected after further selection based on set selection criteria, and 35 articles were considered relevant to the study. The study shows that four predominant areas of cloud computing—cloud security, cloud interoperability, cloud resources and service description, and cloud services discovery and selection—have attracted the attention of researchers as dominant areas where cloud ontologies have made great impact. The proposed methods in the literature applied 30 ontologies in the cloud domain, and five of the methods are still practiced in the legacy computing environment. From the analysis, it was found that several challenges exist, including those related to the application of ontologies to enhance business operations in the cloud and multi-cloud. Based on this review, the study summarizes some unresolved challenges and possible future directions for cloud ontology researchers.

Discovery of Cloud Applications from Logs

“…Moreover, there is a lack of a scientifically systematic treatment of the AD problem especially from the perspectives of unsupervised ways of learning the nature of cloud assets/objects. On the other hand, researchers are focused more on designing frameworks for the discovery of relevant cloud services for a given application rather than categorizing compute instances in a cloud environment subject to common behaviors of its components, as we observe in the review paper by Agbaegbu et al [18] on ontologies in cloud computing and the respective references [19][20][21][22][23][24] therein.…”

Towards a Reference Architecture for Semantic Interoperability in Multi-Cloud Platforms

“…Current literature agrees that ontologies are the core element of semantic solutions [36,26,37,38]. An ontology reflects domain knowledge, where the ontology classes are typically depicted using graphical models, as models are considered to have explicit semantics [39]. Ontologies are often expressed in a formal language that can be interpreted by both humans and machines, like RDF and OWL.…”

Ontology Development for Creating Identical Software Environments to Improve Learning Outcomes in Higher Education Institutions

“…Ontological engineering principles cover many aspects of software in traditional computing, and a certain number of published papers can be found in the literature [25]. However, there is still significant potential for further advancement, especially when considering systems designed for higher education, which exhibit a high degree of heterogeneity in the computer environment.…”