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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 - 21 June 2023

    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, More >

  • Open Access

    ARTICLE

    The Cloud Manufacturing Resource Scheduling Optimization Method Based on Game Theory

    Xiaoxuan Yang*, Zhou Fang

    Journal on Artificial Intelligence, Vol.4, No.4, pp. 229-243, 2022, DOI:10.32604/jai.2022.035368 - 25 May 2023

    Abstract In order to optimize resource integration and optimal scheduling problems in the cloud manufacturing environment, this paper proposes to use load balancing, service cost and service quality as optimization goals for resource scheduling, however, resource providers have resource utilization requirements for cloud manufacturing platforms. In the process of resource optimization scheduling, the interests of all parties have conflicts of interest, which makes it impossible to obtain better optimization results for resource scheduling. Therefore, a multithreaded auto-negotiation method based on the Stackelberg game is proposed to resolve conflicts of interest in the process of resource scheduling.… More >

  • Open Access

    ARTICLE

    Dynamic Intelligent Supply-Demand Adaptation Model Towards Intelligent Cloud Manufacturing

    Yanfei Sun1, Feng Qiao2, Wei Wang1, Bin Xu1, Jianming Zhu1, Romany Fouad Mansour3, Jin Qi1,*

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2825-2843, 2022, DOI:10.32604/cmc.2022.026574 - 29 March 2022

    Abstract As a new mode and means of smart manufacturing, smart cloud manufacturing (SCM) faces great challenges in massive supply and demand, dynamic resource collaboration and intelligent adaptation. To address the problem, this paper proposes an SCM-oriented dynamic supply-demand (S-D) intelligent adaptation model for massive manufacturing services. In this model, a collaborative network model is established based on the properties of both the supply-demand and their relationships; in addition, an algorithm based on deep graph clustering (DGC) and aligned sampling (AS) is used to divide and conquer the large adaptation domain to solve the problem of… More >

  • Open Access

    ARTICLE

    A Homogeneous Cloud Task Distribution Method Based on an Improved Leapfrog Algorithm

    Yunliang Huo1, Ji Xiong1,*, Zhixing Guo1, Qianbing You1, Yi Peng2

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 359-379, 2021, DOI:10.32604/cmes.2021.015314 - 28 June 2021

    Abstract Cloud manufacturing is a new manufacturing model with crowd-sourcing characteristics, where a cloud alliance composed of multiple enterprises, completes tasks that a single enterprise cannot accomplish by itself. However, compared with heterogeneous cloud tasks, there are relatively few studies on cloud alliance formation for homogeneous tasks. To bridge this gap, a novel method is presented in this paper. First, a homogeneous cloud task distribution model under cloud environment was constructed, where services description, selection and combination were modeled. An improved leapfrog algorithm for cloud task distribution (ILA-CTD) was designed to solve the proposed model. Different More >

  • Open Access

    ARTICLE

    Bilateral Collaborative Optimization for Cloud Manufacturing Service

    Bin Xu1, 2, Yong Tang1, Yi Zhu1, Wenqing Yan1, Cheng He3, Jin Qi1, *

    CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 2031-2042, 2020, DOI:10.32604/cmc.2020.011149 - 30 June 2020

    Abstract Manufacturing service composition of the supply side and scheduling of the demand side are two important components of Cloud Manufacturing, which directly affect the quality of Cloud Manufacturing services. However, the previous studies on the two components are carried out independently and thus ignoring the internal relations and mutual constraints. Considering the two components on both sides of the supply and the demand of Cloud Manufacturing services at the same time, a Bilateral Collaborative Optimization Model of Cloud Manufacturing (BCOM-CMfg) is constructed in this paper. In BCOM-CMfg, to solve the manufacturing service scheduling problem on… More >

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