MSE Research Project Database

Real-time Internet of Things (IoT) for smart transportation


Project Leader: Marimuthu Palaniswami
Staff: Tansu Alpcan, Aravinda Rao
Student: Bigi Phillip
Sponsors: Australian Research Council (ARC)
Primary Contact: Marimuthu Palaniswami (palani@unimelb.edu.au)
Keywords: agent based systems; autonomous systems; Internet of Things (IoT); real-time optimisation; traffic management
Disciplines: Electrical & Electronic Engineering
Domains:
Research Centre: ARC Research Network on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)

The real-time IoT applications have stringent delay requirements when implemented over distributed sensing and communication networks. Their finite-time performance matters much more than asymptotic results in the literature. A good illustrative example is smart traffic control, where sensor-laden vehicles pass through intersections by communicating and remaining at a safe distance from each other, rather than grinding to a halt at traffic lights. Thanks to increased investment in smart city infrastructure and projected penetration of autonomous vehicles, smart intersections are expected to replace traditional traffic lights and become prevalent in the near future. Safe and efficient operation of such systems requires control actions to be taken by each system agent, ie, automated vehicles and road side units, within fraction of a second under local communication and computing limitations. The IoT agents in this scenario clearly must attain global objectives of safety and efficiency in real time.

The overarching aim of the project is to develop new practical algorithms for real-time IoT applications and to investigate novel methods for describing their performance in a finite time.  This project aims to investigate fundamental performance guarantees of real-time IoT systems using methodology from networking, optimisation, game theory, and information theory.

The project addresses the above mentioned two challenges through:

  1. The derivation of performance bounds of finite-time algorithms under communication and computing limitations.
  2. The development and analysis of novel real-time algorithms within these bounds for efficient allocation of limited resources considering incentives and minimum performance constraints.

If you are interested in the project, please contact one of the following staff members:

Further information: https://people.eng.unimelb.edu.au/palani/