Mobility Model of People on Requirement-Based Design in Mobile Wireless Network

Abstract

This paper presents the prediction and analysis of a mobility model of people, in short mobility prediction for the mobile wireless network architecture as the essential part of future wireless market trends. Mobile networks and individual mobile terminals need to act as mobile sensors to extract community mobility patterns and environment prediction. These networks need to accommodate the growing wireless network systems like cellular networks. To show a mobile connectivity and wireless connection in urban mesh-network, we utilized urban mobility simulation time with prediction method, and also investigated a large number of mobility flows. Specific attention was focused upon the formation of mobility trends and the comparison results of simulation time as a function of the prediction parameters such as mobility speed, desired speed and the current location point. We also highlight how to achieve high efficiency by using the neural prediction methods and modeling directly to the mobile wireless network architecture by a software tool and library. Major results of our experimental study demonstrate good scalability and usability of our prediction of mobility model by using a statistical comparison results, and trend of mobility usages.