分布式系统中数据管理的人工智能辅助动态建模

Pub Date : 2022-10-01 DOI:10.4018/ijisscm.313623

Yingjun Wang, Shaoyang He, Yiran Wang

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引用次数: 0

摘要

分布式网络中有许多相互依赖的计算机。在这种方案中，总体拥有成本包括设施，如计算机、控制等;购买硬件;以及工资、电费等运营费用。Strom的使用是运营费用的很大一部分。提出了人工智能辅助数据管理动态建模(AI-DM)框架。高比例的电力使用明显与能源规划不充分有关。本研究建议创建一种多目标方法，利用模糊TOPSIS工具为分布式系统规划多标准软件解决方案的准备工作，作为多标准管理的综合指南。执行结果表明，该策略可以通过权重来牺牲需求。

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

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.

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