Year: 2025
Type: article
Abstract: Fair and efficient resource allocation is a fundamental goal of cloud computing systems. However, diverse user requirements and heterogeneous resource types make it difficult to balance utilization efficiency and user-perceived fairness. To address this challenge, we propose a meta-type-based resource allocation mechanism, GAF-MT, which is based on the principle of asset fairness. GAF-MT introduces meta-types to model structured resource groupings and supports user-specific requirements while reducing fragmentation. We design a scheduling algorithm to find feasible solutions and implement GAF-MT based on GUROBI. Extensive experiments in small-scale and large-scale user environments show that GAF-MT not only ensures fairness, but also significantly improves resource utilization and maintains high performance even under high user loads.
Source: Scientific Reports
Authors: Fengyue Zhang, Chunlei Shi
Institution: Henan University of Urban Construction
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,690
OpenAlex ID: W4415924217