Reactive protocols for unified user profiling for anomaly detection in mobile Ad Hoc networks

The Next Generation mobile network expected to be fully automated to meet the growing need for data rates and quality in communication. These prodigious demands have also increased the amount of data being handled in these wireless networks. The cellular networks can leverage vital data about the user and the network conditions providing all-inclusive visibility and intelligence in communication. Emerging analytic technologies such as big data and neural networks have been used to unearth vital insight from network traffic to assist intelligent models in routing packets. Reactive protocols are an emerging model in the intelligent routing of traffic in ad-hoc networks. In this paper, we first utilize the reactive protocols to route traffic in a wireless network while analyzing anomalous behavior. In the case of anomaly detection in wireless communication, combined performance indicators to identify outliers. The detected outliers been compared with the ground data and routes created using the reactive protocols. The combination of reactive protocols and the key performance indicators in network performance uncovered anomalies leading to segregation of these traffic in routing. From the results, it is evident that an abrupt surge in the traffic indicated an anomaly and identify the areas of interest in a network especially for resource and path allocation and fault avoidance. A MATLAB GUI was used to simulate the reactive protocols for routing of traffic and generation of datasets that analyze in Microsoft Excel to characterize the key performance indicators of the network.