scholarly journals RTED-SD: A Real-Time Edge Detection Scheme for Sybil DDoS in the Internet of Vehicles

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Jiabin Li ◽  
Zhi Xue ◽  
Changlian Li ◽  
Ming Liu
Keyword(s):  
Edge Detection ◽  
Real Time ◽  
The Internet ◽  
Detection Scheme ◽  
Internet Of Vehicles

scholarly journals Stopping Accidents before They Happen: Perceiving Lane-Level Moving Vehicle Danger Regions to Warn Surrounding Drivers and Pedestrians

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Chi Guo ◽  
Guangyi Cao ◽  
Jieru Zeng ◽  
Jinsong Cui ◽  
Rong Peng
Keyword(s):  
Real Time ◽  
Large Scale ◽  
The Internet ◽  
Active Safety ◽  
Internet Of Vehicles ◽  
Moving Vehicle ◽  
Moving Vehicles ◽  
Traditional Service ◽  
New Type ◽  
New System

Perceiving the location of dangerous moving vehicles and broadcasting this information to vehicles nearby are essential to achieve active safety in the Internet of Vehicles (IOV). To address this issue, we implement a real-time high-precision lane-level danger region service for moving vehicles. A traditional service depends on static geofencing and fails to deal with dynamic vehicles. To overcome this defect, we devised a new type of IOV service that manages to track dangerous moving vehicles in real time and recognize their danger regions quickly and accurately. Next, we designed algorithms to distinguish the vehicles in danger regions and broadcast the information to these vehicles. Our system can simultaneously manipulate a mass of danger regions for various dangerous vehicles and broadcast this information to surrounding vehicles at a large scale. This new system was tested in Shanghai, Guangzhou, Wuhan, and other cities; the data analysis is presented in this paper as well.

scholarly journals An Application based Efficient Thread Level Parallelism Scheme on Heterogeneous Multicore Embedded System for Real Time Image Processing.

2020 ◽  
Vol 21 (1) ◽  
pp. 47-56
Author(s):  
K Indragandhi ◽  
Jawahar P K
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Embedded System ◽  
Real Time ◽  
Execution Time ◽  
Image Size ◽  
Multicore Processor ◽  
Detection Scheme ◽  
Thread Level Parallelism ◽  
Level Parallelism

The recent advent of the embedded devices is equipped with multicore processor as it significantly improves the system performance. In order to utilize all the core in multicore processor in an efficient manner, application programs need to be parallelized. An efficient thread level parallelism (ETLP) scheme is proposed in this paper and uses computationally intensive edge detection algorithm for evaluation. Edge detection is the important process in various real time applications namely vehicle detection in traffic control, medical image processing etc. The main objective of ETLP scheme is to reduce the execution time and increase the CPU core utilization. The performance of ETLP scheme is evaluated with basic edge detection scheme (BEDS) for different image size. The experimental results reveal that the proposed ETLP scheme achieves efficiency of 49% and 72% for the image size 300 x 256 and 1024 x 1024 respectively. Furthermore an ETLP scheme reducing 66% execution time for image size 1024 x 1024 when compared with BEDS.

scholarly journals Data Anomaly Detection for Internet of Vehicles Based on Traffic Cellular Automata and Driving Style

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4926 ◽  
Author(s):  
Nan Ding ◽  
Haoxuan Ma ◽  
Chuanguo Zhao ◽  
Yanhua Ma ◽  
Hongwei Ge
Keyword(s):  
Cellular Automata ◽  
Anomaly Detection ◽  
Real Time ◽  
Safety Data ◽  
Gaussian Mixture ◽  
The Internet ◽  
Data Sets ◽  
Driving Style ◽  
Safe Driving ◽  
Internet Of Vehicles

The data validity of safe driving in the Internet of Vehicles (IoV) is the basis of improving the safety of vehicles. Different from a traditional information systems, the data anomaly analysis of vehicle safety driving faces the diversity of data anomaly and the randomness and subjectivity of the driver’s driving behavior. How to combine the characteristics of the IOV data with the driving style analysis to provide effective real-time anomaly data detection has become an important issue in the IOV applications. This paper aims at the critical safety data analysis, considering the large computing cost generated by the real-time anomaly detection of all data in the data package. We preprocess it through the traffic cellular automata model which is built to achieve the ideal abnormal detection effect with limited computing resources. On the basis of this model, the Anomaly Detection based on Driving style (ADD) algorithm is proposed to realize real-time and online detection of anomaly data related to safe driving. Firstly, this paper designs the driving coefficient and proposes a driving style quantization model to represent the driving style of the driver. Then, based on driving style quantization model and vehicle driving state information, a data anomaly detection algorithm is developed by using Gaussian mixture model (GMM). Finally, combining with the application scenarios of multi-vehicle collaboration in the Internet of Vehicles, this paper uses real data sets and simulation data sets to analyze the effectiveness of the proposed ADD algorithm.

scholarly journals Real-Time Performance Evaluation of IEEE 802.11p EDCA Mechanism for IoV in a Highway Environment

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Hong Li ◽  
Qiong Wu ◽  
Jing Fan ◽  
Qiang Fan ◽  
Bo Chang ◽  
...  
Keyword(s):  
Real Time ◽  
Network Performance ◽  
Dynamic Network ◽  
Ieee 802.11P ◽  
The Internet ◽  
Public Infrastructure ◽  
Internet Of Vehicles ◽  
Time Performance ◽  
Time Requirements ◽  
The Internet Of Things

With the development of 5G, the Internet of Vehicles (IoV) evolves to be one important component of the Internet of Things (IoT), where vehicles and public infrastructure communicate with each other through a IEEE 802.11p EDCA mechanism to support four access categories (ACs) to access a channel. Due to the mobility of the vehicles, the network topology is time varying and thus incurs a dynamic network performance. There are many works on the stationary performance of 802.11p EDCA and some on real-time performance, but existing work does not consider real-time performance under extreme highway scenario. In this paper, we consider four ACs defined in the 802.11p EDCA mechanism to evaluate the limit of the real-time network performance in an extreme highway scenario, i.e., all vehicles keep the minimum safety distance between each other. The performance of the model has been demonstrated through simulations. It is found that some ACs can meet real-time requirements while others cannot in the extreme scenario.

scholarly journals RTVD: A Real-Time Volumetric Detection Scheme for DDoS in the Internet of Things

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 36191-36201 ◽  
Author(s):  
Jiabin Li ◽  
Ming Liu ◽  
Zhi Xue ◽  
Xiaochen Fan ◽  
Xiangjian He
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
The Internet ◽  
Detection Scheme ◽  
The Internet Of Things

scholarly journals Blockchain-Based Solutions for UAV-Assisted Connected Vehicle Networks in Smart Cities: A Review, Open Issues, and Future Perspectives

Telecom ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 108-140
Author(s):  
Paulo Álvares ◽  
Lion Silva ◽  
Naercio Magaia
Keyword(s):  
Traffic Congestion ◽  
Resource Constraints ◽  
Smart Cities ◽  
The Internet ◽  
Connected Vehicle ◽  
Sensitive Data ◽  
Internet Of Vehicles ◽  
Smart Vehicles ◽  
Security Properties ◽  
Vehicle Networks

It had been predicted that by 2020, nearly 26 billion devices would be connected to the Internet, with a big percentage being vehicles. The Internet of Vehicles (IoVa) is a concept that refers to the connection and cooperation of smart vehicles and devices in a network through the generation, transmission, and processing of data that aims at improving traffic congestion, travel time, and comfort, all the while reducing pollution and accidents. However, this transmission of sensitive data (e.g., location) needs to occur with defined security properties to safeguard vehicles and their drivers since attackers could use this data. Blockchain is a fairly recent technology that guarantees trust between nodes through cryptography mechanisms and consensus protocols in distributed, untrustful environments, like IoV networks. Much research has been done in implementing the former in the latter to impressive results, as Blockchain can cover and offer solutions to many IoV problems. However, these implementations have to deal with the challenge of IoV node’s resource constraints since they do not suffice for the computational and energy requirements of traditional Blockchain systems, which is one of the biggest limitations of Blockchain implementations in IoV. Finally, these two technologies can be used to build the foundations for smart cities, enabling new application models and better results for end-users.

Toward New Intelligent Architectures for the Internet of Vehicles

2021 ◽  
pp. 193-215
Author(s):  
Léo Mendiboure ◽  
Mohamed Aymen Chalouf ◽  
Francine Krief
Keyword(s):  
The Internet ◽  
Internet Of Vehicles
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