The High-Low Water Mark destage (HLWM) algorithm is widely used to enable cached RAID5 to flush dirty data from its write cache to disks due to the simplicity of its operations. It starts and stops a destaging process based on the two thresholds that are configured at the initialization time with the best knowledge of its underlying storage performance capability and its workload pattern which includes traffic intensity, access patterns, etc. However, each time the current workload varies from the original, the thresholds need to be re-configured with the changed workload. This paper proposes an efficient destage algorithm which automatically re-configures its initial thresholds according to the changed traffic intensity and access patterns, called adaptive thresholding. The core of adaptive thresholding is to define the two thresholds as the multiplication of the referenced increasing and decreasing rates of the write cache occupancy level and the time required to fill and empty the write cache. We implement the proposed algorithm upon an actual RAID system and then verify the ability of the auto-reconfiguration with synthetic workloads having a different level of traffic intensity and access patterns. Performance evaluations under well-known traced workloads reveal that the proposed algorithm reduces disk IO traffic by about 12% with a 6% increase in the overwrite ratio compared with the HLWM algorithm.
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Copy
Young Jin NAM, Chanik PARK, "A Self-Adjusting Destage Algorithm with High-Low Water Mark in Cached RAID5" in IEICE TRANSACTIONS on Information,
vol. E86-D, no. 12, pp. 2527-2535, December 2003, doi: .
Abstract: The High-Low Water Mark destage (HLWM) algorithm is widely used to enable cached RAID5 to flush dirty data from its write cache to disks due to the simplicity of its operations. It starts and stops a destaging process based on the two thresholds that are configured at the initialization time with the best knowledge of its underlying storage performance capability and its workload pattern which includes traffic intensity, access patterns, etc. However, each time the current workload varies from the original, the thresholds need to be re-configured with the changed workload. This paper proposes an efficient destage algorithm which automatically re-configures its initial thresholds according to the changed traffic intensity and access patterns, called adaptive thresholding. The core of adaptive thresholding is to define the two thresholds as the multiplication of the referenced increasing and decreasing rates of the write cache occupancy level and the time required to fill and empty the write cache. We implement the proposed algorithm upon an actual RAID system and then verify the ability of the auto-reconfiguration with synthetic workloads having a different level of traffic intensity and access patterns. Performance evaluations under well-known traced workloads reveal that the proposed algorithm reduces disk IO traffic by about 12% with a 6% increase in the overwrite ratio compared with the HLWM algorithm.
URL: https://global.ieice.org/en_transactions/information/10.1587/e86-d_12_2527/_p
Copy
@ARTICLE{e86-d_12_2527,
author={Young Jin NAM, Chanik PARK, },
journal={IEICE TRANSACTIONS on Information},
title={A Self-Adjusting Destage Algorithm with High-Low Water Mark in Cached RAID5},
year={2003},
volume={E86-D},
number={12},
pages={2527-2535},
abstract={The High-Low Water Mark destage (HLWM) algorithm is widely used to enable cached RAID5 to flush dirty data from its write cache to disks due to the simplicity of its operations. It starts and stops a destaging process based on the two thresholds that are configured at the initialization time with the best knowledge of its underlying storage performance capability and its workload pattern which includes traffic intensity, access patterns, etc. However, each time the current workload varies from the original, the thresholds need to be re-configured with the changed workload. This paper proposes an efficient destage algorithm which automatically re-configures its initial thresholds according to the changed traffic intensity and access patterns, called adaptive thresholding. The core of adaptive thresholding is to define the two thresholds as the multiplication of the referenced increasing and decreasing rates of the write cache occupancy level and the time required to fill and empty the write cache. We implement the proposed algorithm upon an actual RAID system and then verify the ability of the auto-reconfiguration with synthetic workloads having a different level of traffic intensity and access patterns. Performance evaluations under well-known traced workloads reveal that the proposed algorithm reduces disk IO traffic by about 12% with a 6% increase in the overwrite ratio compared with the HLWM algorithm.},
keywords={},
doi={},
ISSN={},
month={December},}
Copy
TY - JOUR
TI - A Self-Adjusting Destage Algorithm with High-Low Water Mark in Cached RAID5
T2 - IEICE TRANSACTIONS on Information
SP - 2527
EP - 2535
AU - Young Jin NAM
AU - Chanik PARK
PY - 2003
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E86-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2003
AB - The High-Low Water Mark destage (HLWM) algorithm is widely used to enable cached RAID5 to flush dirty data from its write cache to disks due to the simplicity of its operations. It starts and stops a destaging process based on the two thresholds that are configured at the initialization time with the best knowledge of its underlying storage performance capability and its workload pattern which includes traffic intensity, access patterns, etc. However, each time the current workload varies from the original, the thresholds need to be re-configured with the changed workload. This paper proposes an efficient destage algorithm which automatically re-configures its initial thresholds according to the changed traffic intensity and access patterns, called adaptive thresholding. The core of adaptive thresholding is to define the two thresholds as the multiplication of the referenced increasing and decreasing rates of the write cache occupancy level and the time required to fill and empty the write cache. We implement the proposed algorithm upon an actual RAID system and then verify the ability of the auto-reconfiguration with synthetic workloads having a different level of traffic intensity and access patterns. Performance evaluations under well-known traced workloads reveal that the proposed algorithm reduces disk IO traffic by about 12% with a 6% increase in the overwrite ratio compared with the HLWM algorithm.
ER -