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  • Open Access

    ARTICLE

    MTC: A Multi-Task Model for Encrypted Network Traffic Classification Based on Transformer and 1D-CNN

    Kaiyue Wang1, Jian Gao1,2,*, Xinyan Lei1

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 619-638, 2023, DOI:10.32604/iasc.2023.036701

    Abstract Traffic characterization (e.g., chat, video) and application identification (e.g., FTP, Facebook) are two of the more crucial jobs in encrypted network traffic classification. These two activities are typically carried out separately by existing systems using separate models, significantly adding to the difficulty of network administration. Convolutional Neural Network (CNN) and Transformer are deep learning-based approaches for network traffic classification. CNN is good at extracting local features while ignoring long-distance information from the network traffic sequence, and Transformer can capture long-distance feature dependencies while ignoring local details. Based on these characteristics, a multi-task learning model that combines Transformer and 1D-CNN for… More >

  • Open Access

    ARTICLE

    Using a Software-Defined Air Interface Algorithm to Improve Service Quality

    Madiraju Sirisha1,*, P. Abdul Khayum2

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1627-1641, 2023, DOI:10.32604/iasc.2023.025980

    Abstract In the digital era, the Narrowband Internet of Things (Nb-IoT) influences the massive Machine-Type-Communication (mMTC) features to establish secure routing among the 5G/6G mobile networks. It supports global coverage to the low-cost IoT devices distributed in terrestrial networks. Its key traffic characteristics include robust uplink, moderate data rate/device, extremely high energy efficiency, prolonging device lifetime, and Quality of Service (QoS). This paper proposes a Deep Reinforcement Learning (DRL) combined software-defined air interface algorithm applied on the switching system, satisfying the user requirement and enabling them with the network resources to extend quality of service by choosing the most appropriate quality… More >

  • Open Access

    ARTICLE

    Deployment of Polar Codes for Mission-Critical Machine-Type Communication Over Wireless Networks

    Najib Ahmed Mohammed1, Ali Mohammed Mansoor1,*, Rodina Binti Ahmad1, Saaidal Razalli Bin Azzuhri2

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 573-592, 2022, DOI:10.32604/cmc.2022.020462

    Abstract Mission critical Machine-type Communication (mcMTC), also referred to as Ultra-reliable Low Latency Communication (URLLC), has become a research hotspot. It is primarily characterized by communication that provides ultra-high reliability and very low latency to concurrently transmit short commands to a massive number of connected devices. While the reduction in physical (PHY) layer overhead and improvement in channel coding techniques are pivotal in reducing latency and improving reliability, the current wireless standards dedicated to support mcMTC rely heavily on adopting the bottom layers of general-purpose wireless standards and customizing only the upper layers. The mcMTC has a significant technical impact on… More >

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