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  • Open Access


    Optimal Data Placement and Replication Approach for SIoT with Edge

    B. Prabhu Shankar1,*, S. Chitra2

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 661-676, 2022, DOI:10.32604/csse.2022.019507

    Abstract Social networks (SNs) are sources with extreme number of users around the world who are all sharing data like images, audio, and video to their friends using IoT devices. This concept is the so-called Social Internet of Things (SIot). The evolving nature of edge-cloud computing has enabled storage of a large volume of data from various sources, and this task demands an efficient storage procedure. For this kind of large volume of data storage, the usage of data replication using edge with geo-distributed cloud service area is suited to fulfill the user’s expectations with low… More >

  • Open Access


    IoT-Cloud Empowered Aerial Scene Classification for Unmanned Aerial Vehicles

    K. R. Uthayan1,*, G. Lakshmi Vara Prasad2, V. Mohan3, C. Bharatiraja4, Irina V. Pustokhina5, Denis A. Pustokhin6, Vicente García Díaz7

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5161-5177, 2022, DOI:10.32604/cmc.2022.021300

    Abstract Recent trends in communication technologies and unmanned aerial vehicles (UAVs) find its application in several areas such as healthcare, surveillance, transportation, etc. Besides, the integration of Internet of things (IoT) with cloud computing environment offers several benefits for the UAV communication. At the same time, aerial scene classification is one of the major research areas in UAV-enabled MEC systems. In UAV aerial imagery, efficient image representation is crucial for the purpose of scene classification. The existing scene classification techniques generate mid-level image features with limited representation capabilities that often end up in producing average results.… More >

  • Open Access


    An Energy Aware Algorithm for Edge Task Offloading

    Ao Xiong1, Meng Chen1,*, Shaoyong Guo1, Yongjie Li2, Yujing Zhao2, Qinghai Ou3, Chuan Liu4, Siwen Xu5, Xiangang Liu6

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1641-1654, 2022, DOI:10.32604/iasc.2022.018881

    Abstract To solve the problem of energy consumption optimization of edge servers in the process of edge task unloading, we propose a task unloading algorithm based on reinforcement learning in this paper. The algorithm observes and analyzes the current environment state, selects the deployment location of edge tasks according to current states, and realizes the edge task unloading oriented to energy consumption optimization. To achieve the above goals, we first construct a network energy consumption model including servers’ energy consumption and link transmission energy consumption, which improves the accuracy of network energy consumption evaluation. Because of More >

  • Open Access


    Efficient Autonomous Defense System Using Machine Learning on Edge Device

    Jaehyuk Cho*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3565-3588, 2022, DOI:10.32604/cmc.2022.020826

    Abstract As a large amount of data needs to be processed and speed needs to be improved, edge computing with ultra-low latency and ultra-connectivity is emerging as a new paradigm. These changes can lead to new cyber risks, and should therefore be considered for a security threat model. To this end, we constructed an edge system to study security in two directions, hardware and software. First, on the hardware side, we want to autonomically defend against hardware attacks such as side channel attacks by configuring field programmable gate array (FPGA) which is suitable for edge computing… More >

  • Open Access


    A Monte Carlo Based COVID-19 Detection Framework for Smart Healthcare

    Tallat Jabeen1,2, Ishrat Jabeen1, Humaira Ashraf2, Nz Jhanjhi3,*, Mamoona Humayun4, Mehedi Masud5, Sultan Aljahdali5

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2365-2380, 2022, DOI:10.32604/cmc.2022.020016

    Abstract COVID-19 is a novel coronavirus disease that has been declared as a global pandemic in 2019. It affects the whole world through person-to-person communication. This virus spreads by the droplets of coughs and sneezing, which are quickly falling over the surface. Therefore, anyone can get easily affected by breathing in the vicinity of the COVID-19 patient. Currently, vaccine for the disease is under clinical investigation in different pharmaceutical companies. Until now, multiple medical companies have delivered health monitoring kits. However, a wireless body area network (WBAN) is a healthcare system that consists of nano sensors… More >

  • Open Access


    Blockchain-Based SQKD and IDS in Edge Enabled Smart Grid Network

    Abdullah Musaed Alkhiari1, Shailendra Mishra2,*, Mohammed AlShehri1

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2149-2169, 2022, DOI:10.32604/cmc.2022.019562

    Abstract Smart Grid is a power grid that improves flexibility, reliability, and efficiency through smart meters. Due to extensive data exchange over the Internet, the smart grid faces many security challenges that have led to data loss, data compromise, and high power consumption. Moreover, the lack of hardware protection and physical attacks reduce the overall performance of the smart grid network. We proposed the BLIDSE model (Blockchain-based secure quantum key distribution and Intrusion Detection System in Edge Enables Smart Grid Network) to address these issues. The proposed model includes five phases: The first phase is blockchain-based… More >

  • Open Access


    Constructing a Deep Image Analysis System Based on Self-Driving and AIoT

    Wen-Tsai Sung1, Sung-Jung Hsiao2,*, Chung-Yen Hsiao1

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1223-1240, 2022, DOI:10.32604/iasc.2022.020746

    Abstract This research is based on the system architecture of Edge Computing in the AIoT (Artificial Intelligence & Internet of Things) field. In terms of receiving data, the authors proposed approach employed the camera module as the video source, the ultrasound module as the distance measurement source, and then compile C++ with Raspberry Pi 4B for image lane analysis, while Jetson Nano uses the YOLOv3 algorithm for image object detection. The analysis results of the two single-board computers are transmitted to Motoduino U1 in binary form via GPIO, which is used for data integration and load… More >

  • Open Access


    Performance Comparison of PoseNet Models on an AIoT Edge Device

    Min-Jun Kim1, Seng-Phil Hong2, Mingoo Kang1, Jeongwook Seo1,*

    Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 743-753, 2021, DOI:10.32604/iasc.2021.019329

    Abstract In this paper, we present an oneM2M-compliant system including an artificial intelligence of things (AIoT) edge device whose principal function is to estimate human poses by using two PoseNet models built on MobileNet v1 and ResNet-50 backbone architectures. Although MobileNet v1 is generally known to be much faster but less accurate than ResNet50, it is necessary to analyze the performances of whole PoseNet models carefully and select one of them suitable for the AIoT edge device. For this reason, we first investigate the computational complexity of the models about their neural network layers and parameters… More >

  • Open Access


    Energy Optimization in Multi-UAV-Assisted Edge Data Collection System

    Bin Xu1,2,3, Lu Zhang1, Zipeng Xu1, Yichuan Liu1, Jinming Chai1, Sichong Qin4, Yanfei Sun1,*

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1671-1686, 2021, DOI:10.32604/cmc.2021.018395

    Abstract In the IoT (Internet of Things) system, the introduction of UAV (Unmanned Aerial Vehicle) as a new data collection platform can solve the problem that IoT devices are unable to transmit data over long distances due to the limitation of their battery energy. However, the unreasonable distribution of UAVs will still lead to the problem of the high total energy consumption of the system. In this work, to deal with the problem, a deployment model of a mobile edge computing (MEC) system based on multi-UAV is proposed. The goal of the model is to minimize… More >

  • Open Access


    Few-Shot Learning for Discovering Anomalous Behaviors in Edge Networks

    Merna Gamal1, Hala M. Abbas2, Nour Moustafa3,*, Elena Sitnikova3, Rowayda A. Sadek1

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1823-1837, 2021, DOI:10.32604/cmc.2021.012877

    Abstract Intrusion Detection Systems (IDSs) have a great interest these days to discover complex attack events and protect the critical infrastructures of the Internet of Things (IoT) networks. Existing IDSs based on shallow and deep network architectures demand high computational resources and high volumes of data to establish an adaptive detection engine that discovers new families of attacks from the edge of IoT networks. However, attackers exploit network gateways at the edge using new attacking scenarios (i.e., zero-day attacks), such as ransomware and Distributed Denial of Service (DDoS) attacks. This paper proposes new IDS based on… More >

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