Manoj Sindhwani¹, Charanjeet Singh^1,*, Rajeshwar Singh²

Computer Systems Science and Engineering, Vol.40, No.2, pp. 455-467, 2022, DOI:10.32604/csse.2022.018498

Abstract With the growth of Vehicular Ad-hoc Networks, many services delivery is gaining more attention from the intelligent transportation system. However, mobility characteristics of vehicular networks cause frequent disconnection of routes, especially during the delivery of data. In both developed and developing countries, a lot of time is consumed due to traffic congestion. This has significant negative consequences, including driver stress due to increased time demand, decreased productivity for various personalized and commercial vehicles, and increased emissions of hazardous gases especially air polluting gases are impacting public health in highly populated areas. Clustering is one of the most powerful strategies for… More >

Ye Yang¹, Xiaofang Li², Dongjie Zhu^3,*, Hao Hu³, Haiwen Du⁴, Yundong Sun⁴, Weiguo Tian³, Yansong Wang³, Ning Cao¹, Gregory M.P. O’Hare⁵

Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 481-494, 2021, DOI:10.32604/iasc.2021.019201

Abstract Smart vehicles use sophisticated sensors to capture real-time data. Due to the weak communication capabilities of wireless sensors, these data need to upload to the cloud for processing. Sensor clouds can resolve these drawbacks. However, there is a large amount of redundant data in the sensor cloud, occupying a large amount of storage space and network bandwidth. Deduplication can yield cost savings by storing one data copy. Chunking is essential because it can determine the performance of deduplication. Content-Defined Chunking (CDC) can effectively solve the problem of chunk boundaries shifted, but it occupies a lot of computing resources and has… More >

Mohana Priya Pitchai¹, Manikandan Ramachandran^1,*, Fadi Al-Turjman², Leonardo Mostarda³

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3947-3966, 2021, DOI:10.32604/cmc.2021.015568

Abstract The Internet of Things plays a predominant role in automating all real-time applications. One such application is the Internet of Vehicles which monitors the roadside traffic for automating traffic rules. As vehicles are connected to the internet through wireless communication technologies, the Internet of Vehicles network infrastructure is susceptible to flooding attacks. Reconfiguring the network infrastructure is difficult as network customization is not possible. As Software Defined Network provide a flexible programming environment for network customization, detecting flooding attacks on the Internet of Vehicles is integrated on top of it. The basic methodology used is crypto-fuzzy rules, in which cryptographic… More >

Najla Al-Nabhan^*, Maha AlDuhaim, Sarah AlHussan, Haifa Abdullah, Mnira AlHaid, Rawan AlDuhaishi

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1831-1845, 2021, DOI:10.32604/cmc.2021.012231

Abstract Simulation is a powerful tool for improving, evaluating and analyzing the performance of new and existing systems. Traffic simulators provide tools for studying transportation systems in smart cities as they describe the evolution of traffic to the highest level of detail. There are many types of traffic simulators that allow simulating traffic in modern cities. The most popular traffic simulation approach is the microscopic traffic simulation because of its ability to model traffic in a realistic manner. In many cities of Saudi Arabia, traffic management represents a major challenge as a result of expansion in traffic demands and increasing number… More >

Tzer-Long Chen¹, Chien-Yun Chang², Yung-Cheng Yao³, Kuo-Chang Chung^4,*

Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 73-82, 2021, DOI:10.32604/iasc.2021.015980

Abstract Artificial intelligence, machine learning, and deep learning have achieved great success in the fields of computer vision and natural language processing, and then extended to various fields, such as biology, chemistry, and civil engineering, including big data in the field of logistics. Therefore, many logistics companies move towards the integration of intelligent transportation systems. Only virtual and physical development can support the sustainable development of the logistics industry. This study aims to: 1.) collect timely information from the block chain, 2.) use deep learning to build a customer database so that sales staff in physical stores can grasp customer preferences,… More >

Adil Mushtaq¹, Muhammad Nadeem Majeed¹, Farhan Aadil², Muhammad Fahad Khan², Sangsoon Lim^3,*

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3795-3814, 2021, DOI:10.32604/cmc.2021.015369

Abstract Body Area Networks (BODYNETs) or Wireless Body Area Networks (WBAN), being an important type of ad-hoc network, plays a vital role in multimedia, safety, and traffic management applications. In BODYNETs, rapid topology changes occur due to high node mobility, which affects the scalability of the network. Node clustering is one mechanism among many others, which is used to overcome this issue in BODYNETs. There are many clustering algorithms used in this domain to overcome this issue. However, these algorithms generate a large number of Cluster Heads (CHs), which results in scarce resource utilization and degraded performance. In this research, an… More >

Thavavel Vaiyapuri¹, Sachi Nandan Mohanty², M. Sivaram³, Irina V. Pustokhina⁴, Denis A. Pustokhin⁵, K. Shankar^6,*

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1881-1897, 2021, DOI:10.32604/cmc.2021.014924

Abstract The latest advancements in highway research domain and increase inthe number of vehicles everyday led to wider exposure and attention towards the development of efficient Intelligent Transportation System (ITS). One of the popular research areas i.e., Vehicle License Plate Recognition (VLPR) aims at determining the characters that exist in the license plate of the vehicles. The VLPR process is a difficult one due to the differences in viewpoint, shapes, colors, patterns, and non-uniform illumination at the time of capturing images. The current study develops a robust Deep Learning (DL)-based VLPR model using Squirrel Search Algorithm (SSA)-based Convolutional Neural Network (CNN),… More >

Weiwei Liu¹, Yang Tang², Fei Yang², Chennan Zhang¹, Dun Cao³, Gwang-jun Kim^{4, *}

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2511-2527, 2020, DOI:10.32604/cmc.2020.09113

Abstract Intelligent Transportation System (ITS) is essential for effective identification of vulnerable units in the transport network and its stable operation. Also, it is necessary to establish an urban transport network vulnerability assessment model with solutions based on Internet of Things (IoT). Previous research on vulnerability has no congestion effect on the peak time of urban road network. The cascading failure of links or nodes is presented by IoT monitoring system, which can collect data from a wireless sensor network in the transport environment. The IoT monitoring system collects wireless data via Vehicle-to-Infrastructure (V2I) channels to simulate key segments and their… More >

Honghao Gao^{1, 2, 5}, Wanqiu Huang^{1, 4}, Xiaoxian Yang³

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 547-559, 2019, DOI:10.31209/2019.100000110

Abstract Path planning is an important topic of research in modern intelligent traffic systems (ITSs). Traditional path planning methods aim to identify the shortest path and recommend this path to the user. However, the shortest path is not always optimal, especially in emergency rescue scenarios. Thus, complex and changeable factors, such as traffic congestion, road construction and traffic accidents, should be considered when planning paths. To address this consideration, the maximum passing probability of a road is considered the optimal condition for path recommendation. In this paper, the traffic network is abstracted as a directed graph. Probabilistic data on traffic flow… More >

Muhammad Waqas^{1, 2}, Shanshan Tu^{1, 3, *}, Sadaqat Ur Rehman¹, Zahid Halim², Sajid Anwar², Ghulam Abbas², Ziaul Haq Abbas⁴, Obaid Ur Rehman⁵

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 359-371, 2020, DOI:10.32604/cmc.2020.09821

Abstract Security threats to smart and autonomous vehicles cause potential consequences such as traffic accidents, economically damaging traffic jams, hijacking, motivating to wrong routes, and financial losses for businesses and governments. Smart and autonomous vehicles are connected wirelessly, which are more attracted for attackers due to the open nature of wireless communication. One of the problems is the rogue attack, in which the attacker pretends to be a legitimate user or access point by utilizing fake identity. To figure out the problem of a rogue attack, we propose a reinforcement learning algorithm to identify rogue nodes by exploiting the channel state… More >