Edge-Computing-Based Trustworthy Data Collection Model in the Internet of Things
Tian Wang, Lei Qiu, Arun Kumar Sangaiah, Anfeng Liu, Md Zakirul Alam Bhuiyan, Ying Ma
Abstract
It is generally accepted that the edge computing paradigm is regarded as capable of satisfying the resource requirements for the emerging mobile applications such as the Internet of Things (IoT) ones. Undoubtedly, the data collected by underlying sensor networks are the foundation of both the IoT systems and IoT applications. However, due to the weakness and vulnerability to attacks of underlying sensor networks, the data collected are usually untrustworthy, which may cause disastrous consequences. In this article, a new model is proposed to collect trustworthy data on the basis of edge computing in the IoT. In this model, the sensor nodes are evaluated from multiple dimensions to obtain accurately quantified trust values. Besides, by mapping the trust value of a node onto a force for the mobile data collector, the best mobility path is generated with high trust. Moreover, a mobile edge data collector is used to visit both the sensors with quantified trust values and collect trustworthy data. The extensive experiment validates that the IoT systems based on trustworthy data collection model gain a significant improvement in their performance, in terms of both system security and energy conservation.