.png){kind=icon}
返回
Multiresource Allocation: Fairness-Efficiency Tradeoffs in a Unifying Framework
.png){kind=icon}
OA
AI
DOI：10.1109/TNET.2012.2233213.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Quantifying the notion of fairness is underexplored when there are multiple types of resources and users request different ratios of the different resources. A typical example is data centers processing jobs with heterogeneous resource requirements on CPU, memory, network bandwidth, etc. In such cases, a tradeoff arises between equitability, or fairness, and efficiency. This paper develops a unifying framework addressing the fairness-efficiency tradeoff in light of multiple types of resources. We develop two families of fairness functions that provide different tradeoffs, characterize the effect of user requests' heterogeneity, and prove conditions under which these fairness measures satisfy the Pareto efficiency, sharing incentive, and envy-free properties. Intuitions behind the analysis are explained in two visualizations of multiresource allocation. We also investigate people's fairness perceptions through an online survey of allocation preferences.
Keyword:
Data center
efficiency
fairness
multiresource allocation
resource allocation
tradeoff
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
I
IF:
3.6
论文数:
4.4K
被引数:
9.5K
机构
引用论文
.png){kind=icon}
Effect of modified Taohongsiwu decoction on patients with chemotherapy-induced hand-foot syndromeOAAI
OAAI分享收藏分享收藏分享收藏分享收藏
查看更多内容