AI-Assisted Dynamic Modelling for Data Management in a Distributed System

Yingjun Wang, Shaoyang He, Yiran Wang

Source Title: International Journal of Information Systems and Supply Chain Management (IJISSCM)15(4)

ISSN: 1935-5726|EISSN: 1935-5734|EISBN13: 9781683180272|DOI: 10.4018/IJISSCM.313623

MLA

Wang, Yingjun, et al. "AI-Assisted Dynamic Modelling for Data Management in a Distributed System." IJISSCM vol.15, no.4 2022: pp.1-18. http://doi.org/10.4018/IJISSCM.313623

APA

Wang, Y., He, S., & Wang, Y. (2022). AI-Assisted Dynamic Modelling for Data Management in a Distributed System. International Journal of Information Systems and Supply Chain Management (IJISSCM), 15(4), 1-18. http://doi.org/10.4018/IJISSCM.313623

Chicago

Wang, Yingjun, Shaoyang He, and Yiran Wang. "AI-Assisted Dynamic Modelling for Data Management in a Distributed System," International Journal of Information Systems and Supply Chain Management (IJISSCM) 15, no.4: 1-18. http://doi.org/10.4018/IJISSCM.313623

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Abstract

There are many interdependent computers available in distributed networks. In such schemes, overall ownership costs comprise facilities, such as computers, controls, etc.; buying hardware; and running expenses such as wages, electrical charges, etc. Strom use is a large part of operating expenses. AI-assisted dynamic modelling for data management (AI-DM) framework is proposed. The high percentage of power use is connected explicitly to inadequate planning of energy. This research suggests creating a multi-objective method to plan the preparation of multi-criteria software solutions for distributed systems using the fuzzy TOPSIS tool as a comprehensive guide to multi-criteria management. The execution results demonstrate that this strategy could then sacrifice requirements by weight.