Toward Unified Cloud Service Discovery for Enhanced Service Identification
Abdullah Alfazi, Quan Z. Sheng, Muhammad Ali Babar, Wenjie Ruan, Yongrui Qin · University of Huddersfield Repository (University of Huddersfield) · 2017
Nowadays cloud services are being increasingly used by professionals. A wide variety of cloud services are being introduced every day, and each of which is designed to serve a set of specific purposes. Currently, there is no cloud service specific search engine or a comprehensive directory that is available online. Therefore, cloud service customers mainly select cloud services based on the word of mouth, which is of low accuracy and lacks expressiveness. In this paper, we propose a comprehensive cloud service search engine to enable users to perform personalized search based on certain criteria including their own intention of use, cost and the features provided. Specifically, our cloud service search engine focuses on: (1) extracting and identifying cloud services automatically from the Web; (2) building a unified model to represent the cloud service features; and (3) prototyping a search engine for online cloud services. To this end, we propose a novel Service Detection and Tracking (SDT) model for modeling Cloud services. Then based on the SDT model, a cloud service search engine (CSSE) is implemented for helping effectively discover cloud services, relevant service features and service costs that are provided by the cloud service providers.