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G-Cloud Monitor: A Cloud Monitoring System for Factory Automation for Sustainable Green Computing

Author

Listed:
  • Hwa-Young Jeong

    (Humanitas College, Kyung Hee University, Seoul 130-701, Korea)

  • Young-Sik Jeong

    (Department of Multimedia Engineering, Dongguk University, Seoul 100-715, Korea)

  • Jong Hyuk Park

    (Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul 139-743, Korea)

Abstract

Green and cloud computing (G-cloud) are new trends in all areas of computing. The G-cloud provides an efficient function, which enables users to access their programs, systems and platforms at anytime and anyplace. Green computing can also yield greener technology by reducing power consumption for sustainable environments. Furthermore, in order to apply user needs to the system development, the user characteristics are regarded as some of the most important factors to be considered in product industries. In this paper, we propose a cloud monitoring system to observe and manage the manufacturing system/factory automation for sustainable green computing. For monitoring systems, we utilized the resources in the G-cloud environments, and hence, it can reduce the amount of system resources and devices, such as system power and processes. In addition, we propose adding a user profile to the monitoring system in order to provide a user-friendly function. That is, this function allows system configurations to be automatically matched to the individual’s requirements, thus increasing efficiency.

Suggested Citation

  • Hwa-Young Jeong & Young-Sik Jeong & Jong Hyuk Park, 2014. "G-Cloud Monitor: A Cloud Monitoring System for Factory Automation for Sustainable Green Computing," Sustainability, MDPI, vol. 6(12), pages 1-12, November.
    • Handle: RePEc:gam:jsusta:v:6:y:2014:i:12:p:8510-8521:d:42783
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    Cited by:

    1. Juha Puttonen & Andrei Lobov & Maria A. Cavia Soto & José L. Martinez Lastra, 2019. "Cloud computing as a facilitator for web service composition in factory automation," Journal of Intelligent Manufacturing, Springer, vol. 30(2), pages 687-700, February.

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