16 Jun Student | Mahdi Saki | Design, Modelling and Simulation
University of Technology Sydney (Supervisor: Mehran Abolhasan)
PhD topic – Ultra-reliable and cost-effective communication infrastructure for future IoT-based railway applications
Internet of things (IoT) is the revolutionary technology in the digital world, with a diverse range of services being created and deployed. One of the major challenges involved in efficiently implementing IoT is the managing and transporting of large volumes of data that this solution generates. Modern approaches for IoT completely rely on cellular networks. As the demand for such networks is massively growing, in this project, we explore other communication methods as alternatives for management and delivery of IoT Data in rail networks. Particularly, the focus will be on developing strategies that utilize the existing trains and the rail network as a mode of data transportation. Furthermore, the project will combine physical delivery of IoT data by trains to strategic collection points in the rail networks with cellular infrastructure to minimize costs and increase communication scalability and efficiency.
- Developed a classifier that could realize critical data from delay-tolerant data in an online manner. Then, for transmission of delay-tolerant data, development of three different models include train-to-station, train-to-train and train-to-wayside communication methods.
- For train-to-station communication method, development of an analytical model that could estimate the amount of offloaded data between trains and stations. The performance of the model was validated through simulation in various scenarios in Omnet network simulator, showing over 98 per cent accuracy.
- For train-to-train communication method, the project proposed a novel mobility model that could provide train traffic traces in real-time. As the proposed mobility model needed no GPS module, it could provide a practical solution when signal from GPS or Assisted-GPS is poor or unavailable such as in urban area or inside tunnels.
- Proposed three algorithms for placement of access points (APs) along a rail line needed for the proposed train-to-wayside communication method. Furthermore, a model was proposed to consider the effects of changes of communication characteristics on the placement of APs for rail lines in different scenarios. The simulation results showed that the proposed approach could improve the efficiency of the system by at least 22 per cent and up to 165 per cent within the different defined scenarios. It also showed that over 250 Gigabit data could be transmitted through T2W communications over common WiFi networks.
Saki, M., Abolhasan, M. and Lipman, J. (2019). A big sensor data offloading scheme in rail networks. In 2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring), Kuala Lumpur, Malaysia, pp. 1–6, April 2019.
Saki, M., Abolhasan, M., & Lipman, J. (2020) A Novel Approach for Big Data Classification and Transportation in Rail Networks. In IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 3, pp. 1239-1249, March 2020.