Supervised machine learning for service providers' classification using multiple criteria in a network architecture environment

Abstract

The service selection in a Next Generation Network field remains a challenging problem for service providers, as they have to satisfy customers and keep their earnings. Given the growing number of telecom service providers, the customer is in a dilemma to choose the right service with a fair price. To do so, we propose in this paper a supervised learning algorithm since it is a classification problem. Based on requirements specified in the contract called Service Level Agreement (SLA) in IP Multimedia Service (IMS) network, we ended up choosing the decision trees algorithm for several reasons that we will explore later in this work. This method will assist users in selecting the right service for a better management of contracts between the involved entities.