Modified Naïve Bayes Classifier for Mode Switching and Mobility Management Using Cellular Networks

Abstract

The innovation of services offered by cellular networks gained the attention of researchers in the communication field. Thus, mobile industries deal with remarkable technological competition regarding service quality. The quality is determined by how superior, consistent, and quick a service is delivered to the user. Thus, mobility management is a basic factor as it deals with imperative information for managing user’s mobility. However, due to the expansion of connected devices, the users are set up densely which inspires the researcher for devising a novel mode switching model. This paper devises a novel mode switching model using the Naive Bayes classifier. Here, the switching of modes is based on certain quality parameters, like link utilization, bandwidth, delay, energy consumption, and signal strength. Whenever the network switches the communication link from cellular-mode to user-mode, it must maintain the quality parameters. For enhancing the performance of network mobility management, a mobility management model is devised in which user mobility is computed. Thus, the proposed method is essential for supporting improved user mobility during communication The proposed mode switching using Naive Bayes classifier provides superior performance with a minimal delay of 0.164 s, maximal power of 58.786 bpm, maximal link utilization ratio of 0.727 and maximal throughput of 1,641,723 respectively.