DCAINov 29, 2022

ReAssigner: A Plug-and-Play Virtual Machine Scheduling Intensifier for Heterogeneous Requests

arXiv:2211.16227v1h-index: 24
Originality Incremental advance
AI Analysis

This addresses scheduling inefficiencies for heterogeneous requests in cloud computing, offering an incremental enhancement to existing schedulers.

The paper tackles the problem of virtual machine scheduling for heterogeneous requests in cloud computing by proposing ReAssigner, a plug-and-play intensifier that pre-assigns roles to physical resources to form virtual clusters, achieving significant scheduling performance improvement on a real dataset from Huawei Cloud.

With the rapid development of cloud computing, virtual machine scheduling has become one of the most important but challenging issues for the cloud computing community, especially for practical heterogeneous request sequences. By analyzing the impact of request heterogeneity on some popular heuristic schedulers, it can be found that existing scheduling algorithms can not handle the request heterogeneity properly and efficiently. In this paper, a plug-and-play virtual machine scheduling intensifier, called Resource Assigner (ReAssigner), is proposed to enhance the scheduling efficiency of any given scheduler for heterogeneous requests. The key idea of ReAssigner is to pre-assign roles to physical resources and let resources of the same role form a virtual cluster to handle homogeneous requests. ReAssigner can cooperate with arbitrary schedulers by restricting their scheduling space to virtual clusters. With evaluations on the real dataset from Huawei Cloud, the proposed ReAssigner achieves significant scheduling performance improvement compared with some state-of-the-art scheduling methods.

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