Effectively Collecting Data for the Location-Based Authentication in Internet of Things.

The concept of Internet of things (IoT) has attracted attention as a key technology for realizing future industrial society. In the future society, numerous “things” with sensors are deployed and connected to networks, and data collected from these devices are used for a wide variety of industrial applications. In this paper, we focus on data collection for location-based authentication system as an application of industrial IoT. The authentication system uses ambient information, which is collected from the devices as unique information at a certain place and a certain time. However, since the ambient information changes continuously, it is required to collect it in real time from multipoint. Thus, we propose an efficient data collection method considering the requirements from the authentication system. The key point is to regulate the network performance for data collection by considering the application requirements. Since the location-based authentication system can be used in many situations and has large expansivity, the proposed work is considered to significantly contribute to the future industrial IoT society. In addition, we demonstrate how to optimize the operation of our proposal by using mathematical analysis. Moreover, the efficiency of our proposed method is validated through numerical results. [ABSTRACT FROM PUBLISHER]