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  • Open Access

    ARTICLE

    QoS-Aware Cloud Service Optimization Algorithm in Cloud Manufacturing Environment

    Wenlong Ma1,2,*, Youhong Xu1, Jianwei Zheng2, Sadaqat ur Rehman3

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1499-1512, 2023, DOI:10.32604/iasc.2023.030484

    Abstract In a cloud manufacturing environment with abundant functionally equivalent cloud services, users naturally desire the highest-quality service(s). Thus, a comprehensive measurement of quality of service (QoS) is needed. Optimizing the plethora of cloud services has thus become a top priority. Cloud service optimization is negatively affected by untrusted QoS data, which are inevitably provided by some users. To resolve these problems, this paper proposes a QoS-aware cloud service optimization model and establishes QoS-information awareness and quantification mechanisms. Untrusted data are assessed by an information correction method. The weights discovered by the variable precision Rough Set, which mined the evaluation indicators… More >

  • Open Access

    ARTICLE

    Survey of Resources Allocation Techniques with a Quality of Service (QoS) Aware in a Fog Computing Environment

    Wan Norsyafizan W. Muhamad1, Kaharudin Dimyati2, Muhammad Awais Javed3, Suzi Seroja Sarnin1,*, Divine Senanu Ametefe1

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 1291-1308, 2023, DOI:10.32604/cmc.2023.037214

    Abstract The tremendous advancement in distributed computing and Internet of Things (IoT) applications has resulted in the adoption of fog computing as today’s widely used framework complementing cloud computing. Thus, suitable and effective applications could be performed to satisfy the applications’ latency requirement. Resource allocation techniques are essential aspects of fog networks which prevent unbalanced load distribution. Effective resource management techniques can improve the quality of service metrics. Due to the limited and heterogeneous resources available within the fog infrastructure, the fog layer’s resources need to be optimised to efficiently manage and distribute them to different applications within the IoT network.… More >

  • Open Access

    ARTICLE

    New Denial of Service Attacks Detection Approach Using Hybridized Deep Neural Networks and Balanced Datasets

    Ouail Mjahed1,*, Salah El Hadaj1, El Mahdi El Guarmah1,2, Soukaina Mjahed1

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 757-775, 2023, DOI:10.32604/csse.2023.039111

    Abstract Denial of Service (DoS/DDoS) intrusions are damaging cyber-attacks, and their identification is of great interest to the Intrusion Detection System (IDS). Existing IDS are mainly based on Machine Learning (ML) methods including Deep Neural Networks (DNN), but which are rarely hybridized with other techniques. The intrusion data used are generally imbalanced and contain multiple features. Thus, the proposed approach aims to use a DNN-based method to detect DoS/DDoS attacks using CICIDS2017, CSE-CICIDS2018 and CICDDoS 2019 datasets, according to the following key points. a) Three imbalanced CICIDS2017-2018-2019 datasets, including Benign and DoS/DDoS attack classes, are used. b) A new technique based… More >

  • Open Access

    ARTICLE

    Hybrid Chameleon and Honey Badger Optimization Algorithm for QoS-Based Cloud Service Composition Problem

    G. Manimala*, A. Chinnasamy

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 393-412, 2023, DOI:10.32604/csse.2023.037066

    Abstract Cloud computing facilitates the great potentiality of storing and managing remote access to services in terms of software as a service (SaaS). Several organizations have moved towards outsourcing over the cloud to reduce the burden on local resources. In this context, the metaheuristic optimization method is determined to be highly suitable for selecting appropriate services that comply with the requirements of the client’s requests, as the services stored over the cloud are too complex and scalable. To achieve better service composition, the parameters of Quality of Service (QoS) related to each service considered to be the best resource need to… More >

  • Open Access

    ARTICLE

    Adaptive Butterfly Optimization Algorithm (ABOA) Based Feature Selection and Deep Neural Network (DNN) for Detection of Distributed Denial-of-Service (DDoS) Attacks in Cloud

    S. Sureshkumar1,*, G .K. D. Prasanna Venkatesan2, R. Santhosh3

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 1109-1123, 2023, DOI:10.32604/csse.2023.036267

    Abstract Cloud computing technology provides flexible, on-demand, and completely controlled computing resources and services are highly desirable. Despite this, with its distributed and dynamic nature and shortcomings in virtualization deployment, the cloud environment is exposed to a wide variety of cyber-attacks and security difficulties. The Intrusion Detection System (IDS) is a specialized security tool that network professionals use for the safety and security of the networks against attacks launched from various sources. DDoS attacks are becoming more frequent and powerful, and their attack pathways are continually changing, which requiring the development of new detection methods. Here the purpose of the study… More >

  • Open Access

    ARTICLE

    BFS-SVM Classifier for QoS and Resource Allocation in Cloud Environment

    A. Richard William1,*, J. Senthilkumar2, Y. Suresh2, V. Mohanraj2

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 777-790, 2023, DOI:10.32604/csse.2023.031753

    Abstract In cloud computing Resource allocation is a very complex task. Handling the customer demand makes the challenges of on-demand resource allocation. Many challenges are faced by conventional methods for resource allocation in order to meet the Quality of Service (QoS) requirements of users. For solving the about said problems a new method was implemented with the utility of machine learning framework of resource allocation by utilizing the cloud computing technique was taken in to an account in this research work. The accuracy in the machine learning algorithm can be improved by introducing Bat Algorithm with feature selection (BFS) in the… More >

  • Open Access

    ARTICLE

    Réflexion sur l’offre de services psychologiques en oncologie et soins palliatifs dans deux centres hospitaliers universitaires montréalais

    C. Defer, M.-S. Bernatchez

    Psycho-Oncologie, Vol.16, No.1, pp. 212-217, 2022, DOI:10.3166/pson-2022-0184

    Abstract Face au cancer et à la fin de vie, la détresse émotionnelle est courante et de mieux en mieux repérée, résultant en de nombreuses demandes de consultation vers nos services psychologiques spécialisés. Les auteures présentent une réflexion sur les différents facteurs qui guident leurs choix d’interventions auprès de la clientèle en oncologie et soins palliatifs rencontrée en contexte hospitalier, le défi étant d’offrir le bon soin au moment opportun à tous les patients en besoin et leurs proches. Le plan de traitement sera adapté selon la sévérité et la nature de la détresse, la nécessité d’intervenir rapidement, la préférence du… More >

  • Open Access

    ARTICLE

    Analyser la structure de dispositifs de mise à disposition de données géographiques

    Application aux enjeux de suivi et de gestion du trait de côte en France

    Johan Desbonnet1 , Françoise Gourmelon1, Christophe Claramunt2

    Revue Internationale de Géomatique, Vol.29, No.1, pp. 57-80, 2019, DOI:10.3166/rig.2019.00079

    Abstract Dans le cadre des enjeux de suivi et de gestion du trait de côte, le besoin d’informations et de connaissances sur le milieu côtier accessibles sur le Web est décrit comme un enjeu majeur. Néanmoins sur cette thématique, la stratégie des promoteurs de dispositifs mettant à disposition de l’information géographique numérique reste encore peu connue. Cet article décrit une approche méthodologique en vue d’étudier le volet technique des possibilités de consultation de l’information géographique sur des dispositifs en ligne susceptibles d’être mobilisés dans le suivi et la gestion du trait de côte en France. L’accès aux données géographiques sur ces… More >

  • Open Access

    ARTICLE

    SARS-CoV2 et cancer : quel impact psychologique ?
    Expérience du service d’oncologie médicale du centre hospitalier universitaire Hassan-II de Fès, Maroc

    L. Amaadour, I. Lahrch, O. Siyouri, K. Oualla, Z. Benbrahim, S. Arifi, C. Aarab, S. El Fakir, N. Mellas

    Psycho-Oncologie, Vol.17, No.1, pp. 38-43, 2023, DOI:10.3166/pson-2022-0221

    Abstract Introduction: La Covid-19 constitue une cause de plusieurs affections mentales, notamment chez les patients atteints de cancer qui sont déjà considérés comme une population vulnérable. Ainsi, l’objectif de la présente étude était d’évaluer les troubles psychologiques des patients suivis pour une maladie tumorale maligne, sous traitement médical systémique, ayant eu une infection au SARS-CoV2 ; ainsi que les conséquences que ces troubles psychologiques peuvent avoir sur l’adhésion aux soins oncologiques.
    Méthode: Il s’agit d’une étude transversale sur une période de quatre mois (pic de la pandémie) menée au département d’oncologie médicale du centre hospitalier universitaire Hassan-II de Fès, Maroc. Les… More >

  • Open Access

    ARTICLE

    Overbooking-Enabled Task Scheduling and Resource Allocation in Mobile Edge Computing Environments

    Jixun Gao1,2, Bingyi Hu2, Jialei Liu3,4,*, Huaichen Wang5, Quanzhen Huang1, Yuanyuan Zhao6

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1-16, 2023, DOI:10.32604/iasc.2023.036890

    Abstract Mobile Edge Computing (MEC) is proposed to solve the needs of Internet of Things (IoT) users for high resource utilization, high reliability and low latency of service requests. However, the backup virtual machine is idle when its primary virtual machine is running normally, which will waste resources. Overbooking the backup virtual machine under the above circumstances can effectively improve resource utilization. First, these virtual machines are deployed into slots randomly, and then some tasks with cooperative relationship are offloaded to virtual machines for processing. Different deployment locations have different resource utilization and average service response time. We want to find… More >

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