Company Filing History:
Years Active: 2022-2023
Title: Lin Guan: Innovator in Data Sharing and IoT Traffic Prediction
Introduction
Lin Guan is a prominent inventor based in Beijing, China. He has made significant contributions to the fields of data sharing and Internet of Things (IoT) traffic prediction. With a total of 2 patents, his work is paving the way for advancements in technology and data management.
Latest Patents
Lin Guan's latest patents include a data sharing method, system, electronic device, and storage medium. This innovative method involves building a trust alliance blockchain, which consists of a main chain and at least one slave chain. Each slave chain corresponds to a specific domain, which includes a leader node. The method establishes a virtual slave chain on the trust alliance blockchain, designating a node as a federated learning node. This allows for joint training on a local federated learning model using data generated within its domain, ultimately leading to a public federated learning model for data sharing among domains.
Another notable patent is the system and method of traffic prediction for IoT nodes. This system includes at least one access node, a transmission network, and a cloud platform. The access node collects traffic data and clusters it into access traffic data and network traffic data. It then inputs the access traffic data into a prediction model to forecast future access traffic. The cloud platform further processes the network traffic data to predict traffic for each node, enhancing the efficiency of IoT networks.
Career Highlights
Lin Guan is affiliated with the Beijing University of Posts and Telecommunications, where he continues to contribute to research and innovation in his field. His work is recognized for its potential impact on data sharing and IoT technologies.
Collaborations
Lin collaborates with notable colleagues, including Hui Yang and Chao Li, who share his passion for advancing technology and innovation.
Conclusion
Lin Guan's contributions to data sharing methods and IoT traffic prediction exemplify the importance of innovation in technology. His patents reflect a commitment to enhancing data management and connectivity in an increasingly digital world.