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  • Open Access

    ARTICLE

    Traffic Management in Internet of Vehicles Using Improved Ant Colony Optimization

    Abida Sharif1, Imran Sharif1, Muhammad Asim Saleem2, Muhammad Attique Khan3, Majed Alhaisoni4, Marriam Nawaz5,6, Abdullah Alqahtani7, Ye Jin Kim8, Byoungchol Chang9,*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5379-5393, 2023, DOI:10.32604/cmc.2023.034413 - 29 April 2023

    Abstract The Internet of Vehicles (IoV) is a networking paradigm related to the intercommunication of vehicles using a network. In a dynamic network, one of the key challenges in IoV is traffic management under increasing vehicles to avoid congestion. Therefore, optimal path selection to route traffic between the origin and destination is vital. This research proposed a realistic strategy to reduce traffic management service response time by enabling real-time content distribution in IoV systems using heterogeneous network access. Firstly, this work proposed a novel use of the Ant Colony Optimization (ACO) algorithm and formulated the path More >

  • Open Access

    ARTICLE

    A Shifting Strategy for Electric Commercial Vehicles Considering Mass and Gradient Estimation

    Weiguang Zheng1,2,3, Junzhu Zhang1,2, Shanchao Wang2,*, Gaoshan Feng2, Xiaohong Xu2, Qiuxiang Ma2

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 489-508, 2023, DOI:10.32604/cmes.2023.025169 - 23 April 2023

    Abstract The extended Kalman filter (EKF) algorithm and acceleration sensor measurements were used to identify vehicle mass and road gradient in the work. Four different states of fixed mass, variable mass, fixed slope and variable slope were set to simulate real-time working conditions, respectively. A comprehensive electric commercial vehicle shifting strategy was formulated according to the identification results. The co-simulation results showed that, compared with the recursive least square (RLS) algorithm, the proposed algorithm could identify the real-time vehicle mass and road gradient quickly and accurately. The comprehensive shifting strategy formulated had the following advantages, e.g., More > Graphic Abstract

    A Shifting Strategy for Electric Commercial Vehicles Considering Mass and Gradient Estimation

  • Open Access

    ARTICLE

    Toward Optimal Periodic Crowd Tracking via Unmanned Aerial Vehicle

    Khalil Chebil1,2, Skander Htiouech3, Mahdi Khemakhem1,2,4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 233-263, 2023, DOI:10.32604/cmes.2023.026476 - 23 April 2023

    Abstract Crowd management and analysis (CMA) systems have gained a lot of interest in the vulgarization of unmanned aerial vehicles (UAVs) use. Crowd tracking using UAVs is among the most important services provided by a CMA. In this paper, we studied the periodic crowd-tracking (PCT) problem. It consists in using UAVs to follow-up crowds, during the life-cycle of an open crowded area (OCA). Two criteria were considered for this purpose. The first is related to the CMA initial investment, while the second is to guarantee the quality of service (QoS). The existing works focus on very… More >

  • Open Access

    ARTICLE

    Intelligent Sound-Based Early Fault Detection System for Vehicles

    Fawad Nasim1,2,*, Sohail Masood1,2, Arfan Jaffar1,2, Usman Ahmad1, Muhammad Rashid3

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3175-3190, 2023, DOI:10.32604/csse.2023.034550 - 03 April 2023

    Abstract An intelligent sound-based early fault detection system has been proposed for vehicles using machine learning. The system is designed to detect faults in vehicles at an early stage by analyzing the sound emitted by the car. Early detection and correction of defects can improve the efficiency and life of the engine and other mechanical parts. The system uses a microphone to capture the sound emitted by the vehicle and a machine-learning algorithm to analyze the sound and detect faults. A possible fault is determined in the vehicle based on this processed sound. Binary classification is… More >

  • Open Access

    ARTICLE

    Optimization of Resource Allocation in Unmanned Aerial Vehicles Based on Swarm Intelligence Algorithms

    Siling Feng1, Yinjie Chen1, Mengxing Huang1,2,*, Feng Shu1

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4341-4355, 2023, DOI:10.32604/cmc.2023.037154 - 31 March 2023

    Abstract Due to their adaptability, Unmanned Aerial Vehicles (UAVs) play an essential role in the Internet of Things (IoT). Using wireless power transfer (WPT) techniques, an UAV can be supplied with energy while in flight, thereby extending the lifetime of this energy-constrained device. This paper investigates the optimization of resource allocation in light of the fact that power transfer and data transmission cannot be performed simultaneously. In this paper, we propose an optimization strategy for the resource allocation of UAVs in sensor communication networks. It is a practical solution to the problem of marine sensor networks… More >

  • Open Access

    ARTICLE

    SDN-Enabled Content Dissemination Scheme for the Internet of Vehicles

    Abida Sharif1, Muhammad Imran Sharif1, Muhammad Attique Khan2, Nisar Ali2, Abdullah Alqahtani3, Majed Alhaisoni4, Ye Jin Kim5, Byoungchol Chang6,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2383-2396, 2023, DOI:10.32604/cmc.2023.033894 - 31 March 2023

    Abstract The content-centric networking (CCN) architecture allows access to the content through name, instead of the physical location where the content is stored, which makes it a more robust and flexible content-based architecture. Nevertheless, in CCN, the broadcast nature of vehicles on the Internet of Vehicles (IoV) results in latency and network congestion. The IoV-based content distribution is an emerging concept in which all the vehicles are connected via the internet. Due to the high mobility of vehicles, however, IoV applications have different network requirements that differ from those of many other networks, posing new challenges. More >

  • Open Access

    ARTICLE

    MCMOD: The Multi-Category Large-Scale Dataset for Maritime Object Detection

    Zihao Sun1,*, Xiao Hu2, Yining Qi2, Yongfeng Huang2, Songbin Li3

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1657-1669, 2023, DOI:10.32604/cmc.2023.036558 - 06 February 2023

    Abstract The marine environment is becoming increasingly complex due to the various marine vehicles, and the diversity of maritime objects poses a challenge to marine environmental governance. Maritime object detection technology plays an important role in this segment. In the field of computer vision, there is no sufficiently comprehensive public dataset for maritime objects in the contrast to the automotive application domain. The existing maritime datasets either have no bounding boxes (which are made for object classification) or cover limited varieties of maritime objects. To fulfil the vacancy, this paper proposed the Multi-Category Large-Scale Dataset for… More >

  • Open Access

    ARTICLE

    Received Power Based Unmanned Aerial Vehicles (UAVs) Jamming Detection and Nodes Classification Using Machine Learning

    Waleed Aldosari*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1253-1269, 2023, DOI:10.32604/cmc.2023.036111 - 06 February 2023

    Abstract This paper presents a machine-learning method for detecting jamming UAVs and classifying nodes during jamming attacks on Wireless Sensor Networks (WSNs). Jamming is a type of Denial of Service (DoS) attack and intentional interference where a malicious node transmits a high-power signal to increase noise on the receiver side to disrupt the communication channel and reduce performance significantly. To defend and prevent such attacks, the first step is to detect them. The current detection approaches use centralized techniques to detect jamming, where each node collects information and forwards it to the base station. As a… More >

  • Open Access

    ARTICLE

    Prediction of Traffic Volume of Motor Vehicles Based on Mobile Phone Signaling Technology

    Jin Shang1,*, Hailong Su2,*, Kai Hu3, Xin Guo3, Defa Sun3

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 799-814, 2023, DOI:10.32604/cmc.2023.035729 - 06 February 2023

    Abstract Urban traffic volume detection is an essential part of traffic planning in terms of urban planning in China. To improve the statistics efficiency of road traffic volume, this thesis proposes a method for predicting motor vehicle traffic volume on urban roads in small and medium-sized cities during the traffic peak hour by using mobile signal technology. The method is verified through simulation experiments, and the limitations and the improvement methods are discussed. This research can be divided into three parts: Firstly, the traffic patterns of small and medium-sized cities are obtained through a questionnaire survey.… More >

  • Open Access

    ARTICLE

    Connected Vehicles Computation Task Offloading Based on Opportunism in Cooperative Edge Computing

    Duan Xue1,2, Yan Guo1,*, Ning Li1, Xiaoxiang Song1

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 609-631, 2023, DOI:10.32604/cmc.2023.035177 - 06 February 2023

    Abstract The traditional multi-access edge computing (MEC) capacity is overwhelmed by the increasing demand for vehicles, leading to acute degradation in task offloading performance. There is a tremendous number of resource-rich and idle mobile connected vehicles (CVs) in the traffic network, and vehicles are created as opportunistic ad-hoc edge clouds to alleviate the resource limitation of MEC by providing opportunistic computing services. On this basis, a novel scalable system framework is proposed in this paper for computation task offloading in opportunistic CV-assisted MEC. In this framework, opportunistic ad-hoc edge cloud and fixed edge cloud cooperate to… More >

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