Research output per year
Research output per year
The ever-increasing amount of dynamic traffic with variations in both volume and service time will develop quickly in the foreseeable future, to a level that network link reconfigurations are required to support the bursting or abrupt change of network traffic. Optical networks need to be evolved to provide and manage network bandwidth automatically in an on-demand approach. In this project, machine-Learning (ML) technologies will be explored in dynamic optical networks to optimise network function and link bandwidths of optical networks and allocate network resources efficiently. ML-based network analytics and predictions will replace the timeconsuming method of manual link set up. A new mechanism of automatic resource provision and autonomous network management need to be developed to replace the set-and-forget operation model used in current optical networks.
Optical Communications and Signal Processing
23 Sep 2019 → 24 Sep 2020
Award Date: 1 Dec 2020
B.S Electronic Science and Technology, University of Science and Technology of China
1 Sep 2015 → 30 Jun 2019
Award Date: 30 Jun 2019
Interaction Design, National University of Singapore
12 Jul 2016 → 10 Aug 2016
Award Date: 10 Aug 2016
Research output: Contribution to conference › Conference Paper › peer-review
Research output: Contribution to conference › Conference Paper › peer-review
Research output: Contribution to journal › Letter (Academic Journal) › peer-review