A Stochastic Approach of Dependency Evaluation for IoT Devices

Abstract

Internet of things (IoT) is an emerging technique that offers advanced connectivity of devices, systems, services, and human beings. With the rapid development of hardware and network technologies, the IoT can refer to a wide variety and large number of devices, resulting in complex relationships among IoT devices. The dependencies among IoT devices, which reflect their relationships, are with reference value for the design, development and management of IoT devices. This paper proposes a stochastic model based approach for evaluating the dependencies of IoT devices. A random walk model is proposed to describe the relationships of IoT devices, and its corresponding Markov chain is obtained for dependency analysis. A framework as well as schemes and algorithms for dependency evaluation in real-world IoT are designed based on traffic measurement. Simulation experiments based on real-life data extracted from smart home environments are conducted to illustrate the efficacy of the approach.