.png){kind=icon}
.png){kind=icon}
Return
SDN-Enabled Network Coding-Based Secure Data Dissemination in VANET Environment
.png){kind=icon}
PRE
AI
DOI：10.1109/JIOT.2019.2956964.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Security and reliability in data transmission are considered as the challenging concerns in VANET. Software-defined networking (SDN) and network coding (NC) are the two key apprehensions in networking that have caught much attention from both industry and academia in recent years. Decoupling of control plane and data plane in SDN enables the centralized control of the network, providing flexibility to a great extent. On the other hand, NC has shown immense potential for improving robustness and security when deployed on VANET. This article advocates for the design of an architecture which exercises the SDN concept by incorporating NC with multigeneration-mixing (MGM) functionalities to increase reliability as well as security of data transmission in vehicular networks. We design an MGM-based NC protocol for encoding and decoding of data. Moreover, a centralized SDN controller takes charge of authentication of vehicles. Finally, we build a simulation model based on realistic traffic and communication characteristics. The simulation results show that the proposed protocol leveraged by the SDN framework outperforms the conventional NC-based protocol in case of security and reliability. Moreover, the simulation model is exhibited and point-by-point execution assessment is given to demonstrate the scalability and prevalence of the proposed strategy.
Keywords:
Network coding
Reliability
Security
Data dissemination
Protocols
Vehicular ad hoc networks
Computer network reliability
Data dissemination
intelligent transportation system (ITS)
network coding (NC)
multigeneration mixing (MGM)
reliability
security
software-defined networks
VANET
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
8.9
Papers:
1.4W
Citations:
7.8W
