Time-Aware QoS Web Service Selection Using Collaborative Filtering: A Literature Review.

The large increase in the number of available Web services makes the selection of suitable services a big challenge. Several methods have been developed to predict the Quality of Service (QoS) values in order to solve the service selection problem. However, these methods face many limitations that hinder their prediction accuracy. A particular issue is the dynamic nature of the service environment, which causes variations in QoS values (due to network load, hardware problems, etc.). To overcome, QoS selection methods have utilized contextual information, of the surrounding environments, such as service invocation time and/or user and service locations. Amongst these methods are Collaborative Filtering(CF). In the last few years, several CF methods have augmented service invocation time in their prediction process, forming, what is popularly known as, time-aware CF methods. However, current research lacks a dedicated and comprehensive literature review on time-aware CF prediction methods. To this end, this paper analysed the literature and reviewed forty (40) most prominent studies in this field. It provides a thematic categorization of these studies and an insightful analysis detailing their objectives, benefits, and limitations. It identifies the main research gaps and possible research directions for future work. The literature review provides a state-of-the-art update for researchers pursuing research in service oriented computing.