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  • Open Access

    ARTICLE

    Reliable Failure Restoration with Bayesian Congestion Aware for Software Defined Networks

    Babangida Isyaku1,2,*, Kamalrulnizam Bin Abu Bakar1, Wamda Nagmeldin3, Abdelzahir Abdelmaboud4, Faisal Saeed5,6, Fuad A. Ghaleb1

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3729-3748, 2023, DOI:10.32604/csse.2023.034509

    Abstract Software Defined Networks (SDN) introduced better network management by decoupling control and data plane. However, communication reliability is the desired property in computer networks. The frequency of communication link failure degrades network performance, and service disruptions are likely to occur. Emerging network applications, such as delay-sensitive applications, suffer packet loss with higher Round Trip Time (RTT). Several failure recovery schemes have been proposed to address link failure recovery issues in SDN. However, these schemes have various weaknesses, which may not always guarantee service availability. Communication paths differ in their roles; some paths are critical because of the higher frequency usage.… More >

  • Open Access

    ARTICLE

    Bayesian Rule Modeling for Interpretable Mortality Classification of COVID-19 Patients

    Jiyoung Yun, Mainak Basak, Myung-Mook Han*

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 2827-2843, 2021, DOI:10.32604/cmc.2021.017266

    Abstract Coronavirus disease 2019 (COVID-19) has been termed a “Pandemic Disease” that has infected many people and caused many deaths on a nearly unprecedented level. As more people are infected each day, it continues to pose a serious threat to humanity worldwide. As a result, healthcare systems around the world are facing a shortage of medical space such as wards and sickbeds. In most cases, healthy people experience tolerable symptoms if they are infected. However, in other cases, patients may suffer severe symptoms and require treatment in an intensive care unit. Thus, hospitals should select patients who have a high risk… More >

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