RADiCe:数据中心的风险分析框架

IF 6.2 2区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS Future Generation Computer Systems-The International Journal of Escience Pub Date : 2025-01-04 DOI:10.1016/j.future.2024.107702
Fabian Mastenbroek , Tiziano De Matteis , Vincent van Beek , Alexandru Iosup
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引用次数: 0

摘要

数据中心服务提供商面临着涉及许多风险方面的工程和运营挑战。错误的决策可能导致经济处罚、竞争劣势和不可持续的环境影响。风险管理是现代数据中心设计和操作的一个组成部分,但是缺少允许用户方便地考虑各种风险权衡的框架。我们提出RADiCe,这是一个开源框架,可以对可持续数据中心中与it相关的操作风险进行数据驱动分析。RADiCe利用监测和环境数据,通过离散事件模拟,协助数据中心专家对风险情景进行系统评估、可视化和优化风险。我们的分析强调了数据中心运营商由于电价和可持续性上涨而面临的日益增加的风险,并展示了RADiCe如何通过优化数据中心的拓扑结构和操作设置来评估和控制这些风险。最终,RADiCe能够以比其他工具快70 - 330倍的速度评估风险情景,为交互式风险探索开辟了可能性。
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RADiCe: A Risk Analysis Framework for Data Centers
Datacenter service providers face engineering and operational challenges involving numerous risk aspects. Bad decisions can result in financial penalties, competitive disadvantage, and unsustainable environmental impact. Risk management is an integral aspect of the design and operation of modern datacenters, but frameworks that allow users to consider various risk trade-offs conveniently are missing. We propose RADiCe, an open-source framework that enables data-driven analysis of IT-related operational risks in sustainable datacenters. RADiCe uses monitoring and environmental data and, via discrete event simulation, assists datacenter experts through systematic evaluation of risk scenarios, visualization, and optimization of risks. Our analyses highlight the increasing risk datacenter operators face due to price surges in electricity and sustainability and demonstrate how RADiCe can evaluate and control such risks by optimizing the topology and operational settings of the datacenter. Eventually, RADiCe can evaluate risk scenarios by a factor 70x–330x faster than others, opening possibilities for interactive risk exploration.
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来源期刊
CiteScore
19.90
自引率
2.70%
发文量
376
审稿时长
10.6 months
期刊介绍: Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.
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