Patil, Sonal Dipak (2022) Efficient Cloud Data Transfer via Prediction and Selective Data Dropping in Three-Tier Distributed Cloud Architecture for Smart Traffic Management. Masters thesis, Dublin, National College of Ireland.
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Abstract
The traffic management system is an important application in today's ever-growing vehicle era. With a large number of closed-circuit television (CCTV) cameras available as the Edge node, it is possible to get information about the traffic on roads using these cameras. Also, with the advancement of the latest automobile sensors, it is possible to get the data from the vehicle so that better traffic management can be achieved. In the current work, we propose using a combinational approach that takes information from CCTV cameras and automobile sensors, which allows for smart traffic management. Our focus is on reducing the amount of data transmitted from the sensor to the cloud for further computation. The solution is based on a three-tier architecture of Edge-Fog-Cloud. We could remove 95% of the data transmitted at the edge and roughly 99% of the data on the fog side without affecting accuracy. The overall error was less than 0.07 after applying an autoregression (AR) prediction algorithm to reduced time-series data. We expect that our work can be further expanded to achieve more data reduction. The proposed approach can be used in other application areas as well, such as hospital management, smart farming, etc.
Item Type: | Thesis (Masters) |
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Supervisors: | Name Email Mijumbi, Rashid UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > TL Motor vehicles. Aeronautics. Astronautics T Technology > T Technology (General) > Information Technology > Cloud computing |
Divisions: | School of Computing > Master of Science in Cloud Computing |
Depositing User: | Tamara Malone |
Date Deposited: | 19 Apr 2023 13:02 |
Last Modified: | 19 Apr 2023 13:02 |
URI: | https://norma.ncirl.ie/id/eprint/6482 |
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