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  • Open Access


    A New Hybrid Hierarchical Parallel Algorithm to Enhance the Performance of Large-Scale Structural Analysis Based on Heterogeneous Multicore Clusters

    Gaoyuan Yu1, Yunfeng Lou2, Hang Dong3, Junjie Li1, Xianlong Jin1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 135-155, 2023, DOI:10.32604/cmes.2023.025166

    Abstract Heterogeneous multicore clusters are becoming more popular for high-performance computing due to their great computing power and cost-to-performance effectiveness nowadays. Nevertheless, parallel efficiency degradation is still a problem in large-scale structural analysis based on heterogeneous multicore clusters. To solve it, a hybrid hierarchical parallel algorithm (HHPA) is proposed on the basis of the conventional domain decomposition algorithm (CDDA) and the parallel sparse solver. In this new algorithm, a three-layer parallelization of the computational procedure is introduced to enable the separation of the communication of inter-nodes, heterogeneous-core-groups (HCGs) and inside-heterogeneous-core-groups through mapping computing tasks to various hardware layers. This approach can… More >

  • Open Access


    Transparent Access to Heterogeneous IoT Based on Virtual Resources

    Wenquan Jin1, Sunhwan Lim2, Young-Ho Suh2, Chanwon Park2, Dohyeun Kim3,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4983-4999, 2023, DOI:10.32604/cmc.2023.020851

    Abstract The Internet of Things (IoT) inspires industries to deploy a massive number of connected devices to provide smart and ubiquitous services to influence our daily life. Edge computing leverages sufficient computation and storage at the edge of the network to enable deploying complex functions closer to the environment using Internet-connected devices. According to the purpose of the environment including privacy level, domain functionality, network scale and service quality, various environment-specific services can be provided through heterogeneous applications with sensors and actuators based on edge computing. However, for providing user-friendly service scenarios based on the transparent access to heterogeneous devices in… More >

  • Open Access


    Displacement Field Variable Modeling Method for Heterogeneous Materials in Wind Power Blade Core Plates

    Ying He, Yongshuang Wen*, Xuemei Huang, Leian Zhang, Rujun Song, Chang Li

    Energy Engineering, Vol.120, No.2, pp. 445-459, 2023, DOI:10.32604/ee.2022.022223

    Abstract In order to study the mechanical properties of the heterogeneous core plate of the wind turbine blade, a modeling method of the core plate based on displacement field variables is proposed. Firstly, the wind turbine blade core plate was modeled according to the theory of modeling heterogeneous material characteristics. Secondly, the three-point bending finite element model of the wind turbine blade core plate was solved by the display dynamic equation to obtain the deformation pattern and force-deformation relationship of the core plate. Finally, the three-point bending static test was conducted to compare with the finite element analysis. The test results… More >

  • Open Access


    Heterogeneous Ensemble Feature Selection Model (HEFSM) for Big Data Analytics

    M. Priyadharsini1,*, K. Karuppasamy2

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 2187-2205, 2023, DOI:10.32604/csse.2023.031115

    Abstract Big Data applications face different types of complexities in classifications. Cleaning and purifying data by eliminating irrelevant or redundant data for big data applications becomes a complex operation while attempting to maintain discriminative features in processed data. The existing scheme has many disadvantages including continuity in training, more samples and training time in feature selections and increased classification execution times. Recently ensemble methods have made a mark in classification tasks as combine multiple results into a single representation. When comparing to a single model, this technique offers for improved prediction. Ensemble based feature selections parallel multiple expert’s judgments on a… More >

  • Open Access


    Automated File Labeling for Heterogeneous Files Organization Using Machine Learning

    Sagheer Abbas1, Syed Ali Raza1,2, M. A. Khan3, Muhammad Adnan Khan4,*, Atta-ur-Rahman5, Kiran Sultan6, Amir Mosavi7,8,9

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3263-3278, 2023, DOI:10.32604/cmc.2023.032864

    Abstract File labeling techniques have a long history in analyzing the anthological trends in computational linguistics. The situation becomes worse in the case of files downloaded into systems from the Internet. Currently, most users either have to change file names manually or leave a meaningless name of the files, which increases the time to search required files and results in redundancy and duplications of user files. Currently, no significant work is done on automated file labeling during the organization of heterogeneous user files. A few attempts have been made in topic modeling. However, one major drawback of current topic modeling approaches… More >

  • Open Access


    A Fused Machine Learning Approach for Intrusion Detection System

    Muhammad Sajid Farooq1, Sagheer Abbas1, Atta-ur-Rahman2, Kiran Sultan3, Muhammad Adnan Khan4,*, Amir Mosavi5,6,7

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2607-2623, 2023, DOI:10.32604/cmc.2023.032617

    Abstract The rapid growth in data generation and increased use of computer network devices has amplified the infrastructures of internet. The interconnectivity of networks has brought various complexities in maintaining network availability, consistency, and discretion. Machine learning based intrusion detection systems have become essential to monitor network traffic for malicious and illicit activities. An intrusion detection system controls the flow of network traffic with the help of computer systems. Various deep learning algorithms in intrusion detection systems have played a prominent role in identifying and analyzing intrusions in network traffic. For this purpose, when the network traffic encounters known or unknown… More >

  • Open Access


    Improvised Seagull Optimization Algorithm for Scheduling Tasks in Heterogeneous Cloud Environment

    Pradeep Krishnadoss*, Vijayakumar Kedalu Poornachary, Parkavi Krishnamoorthy, Leninisha Shanmugam

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2461-2478, 2023, DOI:10.32604/cmc.2023.031614

    Abstract Well organized datacentres with interconnected servers constitute the cloud computing infrastructure. User requests are submitted through an interface to these servers that provide service to them in an on-demand basis. The scientific applications that get executed at cloud by making use of the heterogeneous resources being allocated to them in a dynamic manner are grouped under NP hard problem category. Task scheduling in cloud poses numerous challenges impacting the cloud performance. If not handled properly, user satisfaction becomes questionable. More recently researchers had come up with meta-heuristic type of solutions for enriching the task scheduling activity in the cloud environment.… More >

  • Open Access


    Analysis on D2D Heterogeneous Networks with State-Dependent Priority Traffic

    Guangjun Liang1,2, Jianfang Xin3,*, Linging Xia1, Xueli Ni1,4, Yi Cao5

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2981-2998, 2023, DOI:10.32604/cmc.2023.028597

    Abstract In this work, we consider the performance analysis of state dependent priority traffic and scheduling in device to device (D2D) heterogeneous networks. There are two priority transmission types of data in wireless communication, such as video or telephone, which always meet the requirements of high priority (HP) data transmission first. If there is a large amount of low priority (LP) data, there will be a large amount of LP data that cannot be sent. This situation will cause excessive delay of LP data and packet dropping probability. In order to solve this problem, the data transmission process of high priority… More >

  • Open Access


    Millimeter Wave Massive MIMO Heterogeneous Networks Using Fuzzy-Based Deep Convolutional Neural Network (FDCNN)

    Hussain Alaaedi*, Masoud Sabaei

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 633-646, 2023, DOI:10.32604/iasc.2023.032462

    Abstract Enabling high mobility applications in millimeter wave (mmWave) based systems opens up a slew of new possibilities, including vehicle communications in addition to wireless virtual/augmented reality. The narrow beam usage in addition to the millimeter waves sensitivity might block the coverage along with the reliability of the mobile links. In this research work, the improvement in the quality of experience faced by the user for multimedia-related applications over the millimeter-wave band is investigated. The high attenuation loss in high frequencies is compensated with a massive array structure named Multiple Input and Multiple Output (MIMO) which is utilized in a hyperdense… More >

  • Open Access


    Cluster Head Selection and Multipath Routing Based Energy Efficient Wireless Sensor Network

    T. Shanmugapriya1,*, Dr. K. Kousalya2

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 879-894, 2023, DOI:10.32604/iasc.2023.032074

    Abstract The Wireless Sensor Network (WSN) is a network of Sensor Nodes (SN) which adopt radio signals for communication amongst themselves. There is an increase in the prominence of WSN adaptability to emerging applications like the Internet of Things (IoT) and Cyber-Physical Systems (CPS). Data security, detection of faults, management of energy, collection and distribution of data, network protocol, network coverage, mobility of nodes, and network heterogeneity are some of the issues confronted by WSNs. There is not much published information on issues related to node mobility and management of energy at the time of aggregation of data. Towards the goal… More >

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