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  • Open Access

    ARTICLE

    Modified Neural Network Used for Host Utilization Predication in Cloud Computing Environment

    Arif Ullah1, Siti Fatimah Abdul Razak2,*, Sumendra Yogarayan2, Md Shohel Sayeed2

    CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5185-5204, 2025, DOI:10.32604/cmc.2025.059355 - 06 March 2025

    Abstract Networking, storage, and hardware are just a few of the virtual computing resources that the infrastructure service model offers, depending on what the client needs. One essential aspect of cloud computing that improves resource allocation techniques is host load prediction. This difficulty means that hardware resource allocation in cloud computing still results in hosting initialization issues, which add several minutes to response times. To solve this issue and accurately predict cloud capacity, cloud data centers use prediction algorithms. This permits dynamic cloud scalability while maintaining superior service quality. For host prediction, we therefore present a… More >

  • Open Access

    ARTICLE

    Joint Energy Predication and Gathering Data in Wireless Rechargeable Sensor Network

    I. Vallirathi1,*, S. Ebenezer Juliet2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2349-2360, 2023, DOI:10.32604/csse.2023.024864 - 01 August 2022

    Abstract Wireless Sensor Network (WSNs) is an infrastructure-less wireless network deployed in an increasing number of wireless sensors in an ad-hoc manner. As the sensor nodes could be powered using batteries, the development of WSN energy constraints is considered to be a key issue. In wireless sensor networks (WSNs), wireless mobile chargers (MCs) conquer such issues mainly, energy shortages. The proposed work is to produce an energy-efficient recharge method for Wireless Rechargeable Sensor Network (WRSN), which results in a longer lifespan of the network by reducing charging delay and maintaining the residual energy of the sensor. In… More >

  • Open Access

    ARTICLE

    Simulation, Modeling, and Optimization of Intelligent Kidney Disease Predication Empowered with Computational Intelligence Approaches

    Abdul Hannan Khan1,2, Muhammad Adnan Khan3,*, Sagheer Abbas2, Shahan Yamin Siddiqui1,2, Muhammad Aanwar Saeed4, Majed Alfayad5, Nouh Sabri Elmitwally6,7

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1399-1412, 2021, DOI:10.32604/cmc.2021.012737 - 05 February 2021

    Abstract Artificial intelligence (AI) is expanding its roots in medical diagnostics. Various acute and chronic diseases can be identified accurately at the initial level by using AI methods to prevent the progression of health complications. Kidney diseases are producing a high impact on global health and medical practitioners are suggested that the diagnosis at earlier stages is one of the foremost approaches to avert chronic kidney disease and renal failure. High blood pressure, diabetes mellitus, and glomerulonephritis are the root causes of kidney disease. Therefore, the present study is proposed a set of multiple techniques such… More >

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