A Novel Search Engine for Internet of Everything Based on Dynamic Prediction

摘要

In recent years, with the rapid development of sensing technology and de-ployment of various Internet of Everything devices, it becomes a crucial and practical challenge to enable real-time search queries for objects, data, and services in the Internet of Everything. Moreover, such efficient query processing techniques can provide strong fa-cilitate the research on Internet of Everything security issues. By looking into the unique characteristics in the IoE application environ-ment, such as high heterogeneity, high dynam-ics, and distributed, we develop a novel search engine model, and build a dynamic prediction model of the IoE sensor time series to meet the real-time requirements for the Internet of Everything search environment. We validated the accuracy and effectiveness of the dynamic prediction model using a public sensor dataset from Intel Lab.