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  • Open Access

    ARTICLE

    Resource Based Automatic Calibration System (RBACS) Using Kubernetes Framework

    Tahir Alyas1, Nadia Tabassum2, Muhammad Waseem Iqbal3,*, Abdullah S. Alshahrani4, Ahmed Alghamdi5, Syed Khuram Shahzad6

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1165-1179, 2023, DOI:10.32604/iasc.2023.028815 - 06 June 2022

    Abstract Kubernetes, a container orchestrator for cloud-deployed applications, allows the application provider to scale automatically to match the fluctuating intensity of processing demand. Container cluster technology is used to encapsulate, isolate, and deploy applications, addressing the issue of low system reliability due to interlocking failures. Cloud-based platforms usually entail users define application resource supplies for eco container virtualization. There is a constant problem of over-service in data centers for cloud service providers. Higher operating costs and incompetent resource utilization can occur in a waste of resources. Kubernetes revolutionized the orchestration of the container in the cloud-native… More >

  • Open Access

    ARTICLE

    Clustered Single-Board Devices with Docker Container Big Stream Processing Architecture

    N. Penchalaiah1, Abeer S. Al-Humaimeedy2, Mashael Maashi3, J. Chinna Babu4,*, Osamah Ibrahim Khalaf5, Theyazn H. H. Aldhyani6

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5349-5365, 2022, DOI:10.32604/cmc.2022.029639 - 28 July 2022

    Abstract The expanding amounts of information created by Internet of Things (IoT) devices places a strain on cloud computing, which is often used for data analysis and storage. This paper investigates a different approach based on edge cloud applications, which involves data filtering and processing before being delivered to a backup cloud environment. This Paper suggest designing and implementing a low cost, low power cluster of Single Board Computers (SBC) for this purpose, reducing the amount of data that must be transmitted elsewhere, using Big Data ideas and technology. An Apache Hadoop and Spark Cluster that… More >

  • Open Access

    ARTICLE

    Ant Colony Optimization-based Light Weight Container (ACO-LWC) Algorithm for Efficient Load Balancing

    K. Aruna1,*, G. Pradeep2

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 205-219, 2022, DOI:10.32604/iasc.2022.024317 - 15 April 2022

    Abstract Container technology is the latest lightweight virtualization technology which is an alternate solution for virtual machines. Docker is the most popular container technology for creating and managing Linux containers. Containers appear to be the most suitable medium for use in dynamic development, packaging, shipping and many other information technology environments. The portability of the software through the movement of containers is appreciated by businesses and IT professionals. In the docker container, one or more processes may run simultaneously. The main objective of this work is to propose a new algorithm called Ant Colony Optimization-based Light… More >

  • Open Access

    ARTICLE

    DAVS: Dockerfile Analysis for Container Image Vulnerability Scanning

    Thien-Phuc Doan, Souhwan Jung*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1699-1711, 2022, DOI:10.32604/cmc.2022.025096 - 24 February 2022

    Abstract Container technology plays an essential role in many Information and Communications Technology (ICT) systems. However, containers face a diversity of threats caused by vulnerable packages within container images. Previous vulnerability scanning solutions for container images are inadequate. These solutions entirely depend on the information extracted from package managers. As a result, packages installed directly from the source code compilation, or packages downloaded from the repository, etc., are ignored. We introduce DAVS–A Dockerfile analysis-based vulnerability scanning framework for OCI-based container images to deal with the limitations of existing solutions. DAVS performs static analysis using file extraction based More >

  • Open Access

    ARTICLE

    DL-HAR: Deep Learning-Based Human Activity Recognition Framework for Edge Computing

    Abdu Gumaei1, 2, *, Mabrook Al-Rakhami1, 2, Hussain AlSalman2, Sk. Md. Mizanur Rahman3, Atif Alamri1, 2

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1033-1057, 2020, DOI:10.32604/cmc.2020.011740 - 20 August 2020

    Abstract Human activity recognition is commonly used in several Internet of Things applications to recognize different contexts and respond to them. Deep learning has gained momentum for identifying activities through sensors, smartphones or even surveillance cameras. However, it is often difficult to train deep learning models on constrained IoT devices. The focus of this paper is to propose an alternative model by constructing a Deep Learning-based Human Activity Recognition framework for edge computing, which we call DL-HAR. The goal of this framework is to exploit the capabilities of cloud computing to train a deep learning model More >

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