Edge/Fog Computing System Area

  • Edge Computing is a distributed computing paradigm that brings computation and data storage closer to the sources of data
  • Fog Computing is an architecture that uses edge devices to carry out a substantial amount of computation, storage and communication locally and routed over the Internet backbone
  • The DMS Edge/Fog System team is currently researching about
    • Autonomic Provisioning Edge Cluster System
    • Smart Gateway for onboarding IoT devices to Edge Cluster

Cloud Computing System Area

  • Cloud computing is the delivery of computing resources as a service.
  • Cloud computing can be rapidly provisioned and released with minimal management effort or service provider interaction.
  • Cloud Computing System team is currently researching about
    • Autonomic Provisioning Cloud Computing System for Customization
    • Serverless computing
    • Reinforcementt Learning for Cloud Computing

Deep Reinforcement Learning AI Area

  • Deep reinforcement learning combines two fundamentals of traditional reinforcement learning with deep learning.
  • Our team focus on
    • Developing an efficient Multi-Agent Deep Reinforcement Learning model for operating multiple UAVs and robots
    • Distributed Deep Reinforcement Learning
    • SILS(Software-In-the-Loop Simulation) and HILS(Hardware-In-the-Loop Simulation)of Deep Reinforcement Learning algorithms


Computer Vision AI Area

  • Computer Vision is one of the latest areas of computer science that studies the part of a machine’s vision
  • The DMS Vision team is working on an interactive healthcare cleaning robot system for the Silver Generation.
    • Object detection to detect people
    • Face recognition to recognize a particular user
    • Emotion Recognition for monitoring user emotions
    • Action Recognition to recognize the user’s motion
    • Pose Estimation to perform the user’s exercise assistance role


Natural Language Processsing AI Area


Digital Twin Area

  • Digital twin (DT) is a pioneering technology and a promising game-changer in various emerging industries.
  • The concept of DT opens a world of possibilities for fundamentally the infusion of physical-twin specific computational models which are dynamically updated into a feedback loop of data-driven analysis and decision-making.
  • A digital twin is a set of coupled computational models that gradually transit throughout different states in its featured state-space as time goes on, in which constantly and equivalently represent the real-world structure, behaviors and surrounding context of its physical twin.
  • DMS Group is working on the development of (i) neural digital twin dynamic engines (DTDE), (ii) neural digital twin control engines (DTCE), (iii) digital twin control frame (DTCF) and (iv) digital twin cloud infrastructure (DTCI) for U*V systems.


Dependability and Security Quantification Area

  • Dependability and security are of five distinctive natures (along with functionality, performance, and cost) for computing and communication systems.
  • Computing systems and networks with a sophisticated composition of multi-level systems and things are inevitably prone to a chain of threats (faults, errors, and failures) which eventually causes fatal losses, such as service interruption/outage, data leak, or even human lives.
  • Even a 1% failure rate is too high, because it causes 3.65 days of unscheduled downtime in a year which, in turn, may reduce an enormous amount of enterprise turnover.
  • Therefore, dependability and security requirements should be taken into consideration to obtain the highest level of trustworthiness for computing infrastructures, in practice.
  • DMS Group is working on the quantification methodologies for dependability and security metrics of computing systems and networks: virtualized server systems (VSS), data center networks (DCN), software defined network (SDN), Cloud-Fog-Edge Continuum (CFE), Internet of Medical Things (IoMT), Internet of Industrial Things (IoIT), unmanned aerial systems (UAS) etc.