An Oversubscription and Service Pricing Exploitation-Based Profit Maximization Framework for Industry Cloud Resource Management

📅 2026-08-26
📈 Citations: 0
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🤖 AI Summary
本文提出了一种基于资源超售和服务定价模型的工业云资源管理框架,利用自适应集成机器学习预测虚拟机资源使用情况,并通过模糊C均值聚类减少资源浪费,以提高盈利和运营效率。
📝 Abstract
This article proposed a novel industry cloud resource management framework that exploits resource oversubscription and heterogeneous service pricing models to maximize profitability and operational efficiency for industry cloud providers. The framework proposes an adaptive ensemble machine learning driven prediction model for proactive estimation of resource utilization of Virtual Machines (VM)s based on previous resource utilization of respective users' VMs to minimize resource wastage due to oversubscription by them. Accordingly, the VMs having similar predicted resource usage are grouped using Fuzzy C means clustering. This helps to determine the required number of VMs with specific configuration to be deployed before executing user requests. Concurrently, the framework incorporates two distinct categories of cloud service pricing models, namely the Delay Sensitive Model and the Best-Effort Model. Accordingly, the user requests are classified and executed by selecting the most suitable VMs, with the goal of maximizing revenue and reducing electricity costs in cloud data centers (CDCs). Experimental simulation and comparison against state-of-the-art methods, using two benchmark VM traces, validates the performance of proposed framework. It significantly reduces electricity bills by 55.56 percentage, power consumption and active servers by up to 60.7 percentage and 51 percentage, respectively, while improving resource utilization and profits by up to 60 percentage and 51.18 percentage, respectively
Problem

Research questions and friction points this paper is trying to address.

resource oversubscription
service pricing models
profit maximization
operational efficiency
cloud resource management
Innovation

Methods, ideas, or system contributions that make the work stand out.

resource oversubscription
heterogeneous service pricing models
adaptive ensemble machine learning
Fuzzy C means clustering
profit maximization
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