Recommending cloud services based on social trust: An overview

Abstract

The continued expansion and development of the business requires great computing power and massive data storage systems. Cloud services deliver these resources in a simple, flexible and secure way. There is now a wide range of similar cloud services with different capabilities, which requires a recommendation system. Recommendation based on Quality of Service (QoS) is the first generation of service recommendation systems that only takes into account the rating information of all users without distinction. However, these systems suffer from many shortcomings, such as cold start and data sparsity issues, as well as poor accuracy and reliability of recommendation results. To address these issues and improve the quality of recommendations, a new generation of recommender systems has emerged, such as context-aware, domain-specific, and trust-aware recommender systems. These systems now focus more on how to leverage social data generated from user interactions with each other in social networks to recommend more suitable and reliable services in response to user needs. Due to the importance of considering trust in cloud environments, this study aims to provide an overview of the research on trust-based cloud service recommendation approaches proposed so far and highlights the current trend towards use new technologies such as deep learning to deal with certain challenges.