Research Area: Internet of Things
The Internet-of-Things (IoT) is envisioned as a transformative network paradigm to carry the massive interconnections among ubiquitous physical objects in real life. With the rapid advance in computing hardware industry and the ubiquity of wireless communication networks, the IoT has the potentials to greatly revolutionize the application scenarios and service types of our daily-used devices. However, with billions of devices anticipated to be connected, constructing the future IoT networks faces a series of significant challenges in diverse technical aspects.
In this thesis, we emphasis on endowing the IoT devices with intelligence, and propose several learning-based strategies for resource access and allocation in the communication/computing network design of IoT. Considering the scarce spectrum resource, we first design a novel learning-based spectrum sensing policy for IoT devices to achieve a fast spectrum access for unlicensed spectrum resource with a strong adaptability.
In the last part, we developed an efficient strategy to provision different computing services for IoT devices, which enables an overall improvement in the quality of service (QoS) of smart applications. We concluded the thesis with a summary of important results and insights in our works, which is followed by an extensive discussion on other potential research directions in the scope of IoT for our future works.
Name of the Researcher: Yan, Zun
Name of the Supervisor(s): Li, Yonghui
Year of Completion: 2021
University: The University of Sydney
Thesis Link: Home Page Url
