Ontologies in Cloud Computing—Review and Future Directions

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.

An Efficient Applications Cloud Interoperability Framework Using I-Anfis

Cloud interoperability provides cloud services such as Software as a Service (SaaS) or customer system to communicate between the cloud providers. However, one of the most important barriers for existing researches was to adopt the application’s or data’s in cloud computing environments so as to obtain efficient cloud interoperability. This paper focuses on reliable cloud interoperability with a heterogeneous cloud computing resource environment with the objective of providing unilateral provision computing capabilities of a cloud server without the help of human interaction and allowing proper utilization of applications and services across various domains by using an effective cloud environment available at runtime. Moreover, the framework uses hybrid squirrel search genetic algorithm (HSSGA) to select the relevant features from a set of extracted features in order to eliminate irrelevant data which provides advantages of low computational time and less memory usage. Thereafter, for a proper selection of cloud server with respect to the selected features, the system has developed the improved adaptive neuro-fuzzy inference system (I-ANFIS) which provides accurate server selection and helps against uncertainties caused by servers or applications. Hence, the experimental result of the proposed framework gives an accuracy of 94.24% and remains more efficient compared to existing frameworks.

Methodological Research on Architecture of Cloud Service Models in Cloud Computing

Cloud computing is the most recent association in speaking to computing resources as an assistance. It addresses a move away from figuring as a thing that is gained, to computing as a help that is given to clients over the web from colossal scale data focuses – or "clouds". While cloud computing is expanding making acclaim in the IT business, the academic world appeared to fall behind the speedy movements in this field. In this paper, we investigate cloud building and differences cloud figuring and framework handling. We also address the characteristics and uses of a couple of surely understood cloud computing stages. In this paper, we discuss about the architecture of cloud computing models for which we perceived a couple of troubles from the cloud figuring gathering point of view what's more, we additionally highlighted the cloud interoperability issue that preferences broad future scope & progress.

Privacy and Security in Cloud Computing Architecture

Cloud Computing is the most advanced technical platform for next generation. Cloud Computing provide us a large range of data storage space in web source. Cloud Computing work automatically as per the need of user we don’t need to do extra work on it. High level applications and game is run by Cloud Computing. It simply states that cloud computing means storing and accessing the data and programs over the internet rather than the computer’s hard disk. Cloud Computing cover the wide range of areas. It provides its service through online net connection. The data can be anything such as music, files, images, documents, and more. The user can access the data from anywhere just with the help of an internet connection. To use cloud computing, the user should register and provide with ID and password for security reasons. The speed of transfer depends on various factors such as the capacity of the server, internet speed, and many more. In this paper, we explore the understanding the determinates of security and privacy in cloud computing, Cloud Computing architecture and we also address the characteristics and applications of several popular cloud computing platforms. We identified several challenges from the cloud computing adoption perspective and we also highlighted the cloud interoperability issue that deserves substantial further research and development. However, security and privacy issues present a strong barrier for users to adapt into cloud computing systems.