Abstract
Connected and Automated Vehicles (CAVs) are expected to constantly interact with a network of processing nodes installed in secure cabinets located at the side of the road -- thus, forming Fog Computing-based infrastructure for Intelligent Transportation Systems (ITSs). Future city-scale ITS services will heavily rely upon the sensor data regularly off-loaded by each CAV on the Fog Computing network. Due to the broadcast nature of the medium, CAVs' communications can be vulnerable to eavesdropping. This paper proposes a novel data offloading approach where the Random Linear Network Coding (RLNC) principle is used to ensure the probability of an eavesdropper to recover relevant portions of sensor data is minimized. Our preliminary results confirm the effectiveness of our approach when operated in a large-scale ITS networks.
Original language | English |
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Title of host publication | 2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Number of pages | 2 |
ISBN (Electronic) | 9781728112176 |
ISBN (Print) | 9781728112183 |
DOIs | |
Publication status | Published - 27 Jun 2019 |
Event | 89th IEEE Vehicular Technology Conference, VTC Spring 2019 - Kuala Lumpur, Malaysia Duration: 28 Apr 2019 → 1 May 2019 |
Publication series
Name | IEEE Vehicular Technology Conference |
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Volume | 2019-April |
ISSN (Print) | 1550-2252 |
Conference
Conference | 89th IEEE Vehicular Technology Conference, VTC Spring 2019 |
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Country/Territory | Malaysia |
City | Kuala Lumpur |
Period | 28/04/19 → 1/05/19 |
Bibliographical note
To appear in IEEE VTC-Spring 2019Keywords
- V2X
- CAV
- ITS
- Fog Computing
- Data Offloading
- Secrecy Outage Probability
- Intercept Probability