VDMig: An Adaptive Virtual Disk Migration Scheme for Cloud Block Storage System

In modern cloud block storage systems, the routing layer bears the task of slicing and distributing application requests to the underlying storage engine and thus becomes the critical path. However, skewed application traffic leads to load imbalance among routing servers, causing severe performance bottlenecks and hurting the quality of service. Existing load balancing methods typically employ static allocation strategies without considering the access pattern of individual virtual disks. They are not well suited to deal with the highly dynamic loads in production. In this paper, we first collect and analyze 7-day workload traces of 130k virtual disks from a commercial cloud block storage system. Based on several observations, we propose VDMig, an adaptive virtual disk migration scheme. VDMig initially divides virtual disks into two types of access patterns, then uses application-level semantics to characterize the load of virtual disks, and finally implements predictive migrating strategies adaptively to achieve dynamic load balancing. Extensive experiments demonstrate that VDMig can achieve fine-grained virtual disk management, effectively balancing the load among routing servers. Compared to the static methods widely deployed in the industry, VDMig can reduce the imbalance by 82.38 % on average.

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Publication Details

Published
2024-11-18
DOI
https://doi.org/10.1109/iccd63220.2024.00075
Citations
2
Primary Topic
Caching and Content Delivery
Type
article
Field-Weighted Citation Impact
0.70
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article

VDMig: An Adaptive Virtual Disk Migration Scheme for Cloud Block Storage System

Ke Zhou, Mengling Tao, Song Gao, Guangjie Xing et al.
2 citations
Caching and Content Delivery
0.70
article

VDMig: An Adaptive Virtual Disk Migration Scheme for Cloud Block Storage System

Ke Zhou, Mengling Tao, Song Gao, Guangjie Xing, Hua Wang, Yaodong Han
article en
2 citations

Abstract

In modern cloud block storage systems, the routing layer bears the task of slicing and distributing application requests to the underlying storage engine and thus becomes the critical path. However, skewed application traffic leads to load imbalance among routing servers, causing severe performance bottlenecks and hurting the quality of service. Existing load balancing methods typically employ static allocation strategies without considering the access pattern of individual virtual disks. They are not well suited to deal with the highly dynamic loads in production. In this paper, we first collect and analyze 7-day workload traces of 130k virtual disks from a commercial cloud block storage system. Based on several observations, we propose VDMig, an adaptive virtual disk migration scheme. VDMig initially divides virtual disks into two types of access patterns, then uses application-level semantics to characterize the load of virtual disks, and finally implements predictive migrating strategies adaptively to achieve dynamic load balancing. Extensive experiments demonstrate that VDMig can achieve fine-grained virtual disk management, effectively balancing the load among routing servers. Compared to the static methods widely deployed in the industry, VDMig can reduce the imbalance by 82.38 % on average.

Tencent (China) (CN), Wuhan National Laboratory for Optoelectronics (CN), Huazhong University of Science and Technology (CN)
Reduced inequalities
Openalex Percentile: Top 25%
Caching and Content Delivery
0.70
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