Data Driven Analysis for Web Service Selection

Since web services are among the basic cloud technologies, the problems related to their quality remains of a primary importance. An open question is how to provide services that can justifiably be trusted and at the same time acceptable and usable by the clients. The aim of the present paper is to reveal three conceptually different data-driven approaches for quality of service (QoS) assessment based on quality metrics data. A comparison analysis of the described assessments provides a solid base for reliable QoS service selection. Software tool that enables the three assessments is developed. It ensures a general overview of the compared services according to their quality. Analysis of advantages and drawbacks of the estimations is done both on theoretical perspective and through application by the tool towards real time data of two web services of weather forecasting.