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
Global Navigation involves planning a trajectory for an agent to move from its starting point to a destination using a map. It relies on algorithms that compute the optimal path based on global knowledge of the environment.
Research in this area also includes generating maps in real-time. Techniques like Simultaneous Localization and Mapping (SLAM) allow agents to navigate in unknown or changing environments by building and updating maps as they move.
Local Navigation
Local Navigation guides an agent along the trajectory set by Global Navigation, handling obstacles in real-time. The agent moves toward local goals while avoiding static and moving obstacles.
Our research emphasizes Deep Reinforcement Learning (DRL) for obstacle avoidance. DRL enables the agent to learn and adapt to complex environments, making safe and efficient decisions in dynamic situations.
Digital Twin
Our research focuses on developing Digital Twins, realistic digital replicas of real-world systems, to simulate, test, and train models before real-world deployment.
A key aspect is creating a Digital Twin that closely matches the real environment. We use Unreal Engine to build this simulation, providing a highly realistic platform for testing and optimization.
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 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.