Adaptive Wi-Fi offloading schemes in heterogeneous networks, the survey

Abstract

At present, the need for data traffic is experiencing tremendous growth. The growth of smartphones technology offers new applications. On the other hand, the growth in cellular network access infrastructure has not been able to keep up with the increasing demand for data package services. For this reason, Wi-Fi offloading is needed, namely cellular users, using Wi-Fi access for their data needs. In 2016, global data communication traffic growth reached 63%. Many researchers have proposed the adaptive wireless fidelity (Wi-Fi) offloading (AAWO) algorithm to transfer data on heterogeneous networks. In this study, the proposed adaptive incentive scheme is classified, to obtain an adaptive scheme based on cost, energy, service quality, and others. From the survey results shown, there is no proposed adaptive algorithm based on the quality of experience (QoE). This provides an opportunity for further research where the Wi-Fi offloading scheme uses the perspective user or user experient options. In addition, open research uses artificial intelligence and machine learning methods as adaptive methods.