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Workload Scheduling for Massive Storage Systems with Arbitrary Renewable Supply

delete2018-10-01
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AI
D
Daping Li
X
Xiaoyang Qu
万
万继光 (Jiguang Wan) *
J
Jun Wang
Y
Yang Xia
C
Changsheng Xie
DOI:10.1109/TPDS.2018.2820070delete
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Abstract

Abstract

En 中文
As datacenters grow in scale, increasing energy costs and carbon emissions have led data centers to seek renewable energy, such as wind and solar energy. However, tackling the challenges associated with the intermittency and variability of renewable energy is difficult. This paper proposes a scheme called GreenMatch, which deploys an SSD cache to match green energy supplies with a time-shifting workload schedule while maintaining low latency for online data-intensive services. With the SSD cache, the process for a latency-sensitive request to access a disk is divided into two stages: a low-energy/low-latency online stage and a high-energy/high-latency off-line stage. As the process in the latter stage is off-line, it offers opportunities for time-shifting workload scheduling in response to variations of green energy supplies. We also allocate an HDD cache to guarantee data availability when renewable energy is inadequate. Furthermore, we design a novel replacement policy called Inactive P-disk First for the HDD cache to avoid inactive disk accesses. The experimental results show that GreenMatch can make full use of renewable energy while minimizing the negative impacts of intermittency and variability on performance and availability.
Keywords:
Renewable energy
storage system
SSD cache
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Journal

IEEE Transactions on Parallel and Distributed Systems cover
IEEE Transactions on Parallel and Distributed Systems
IF:
6
Papers:
5.2K
Citations:
1.1W

Organization

State University System of Florida cover
State University System of Florida
Scholars:
12.8W
Papers: 10.9W
Citations: 130
U
University of Central Florida
Scholars:
8.7K
Papers: 6.8K
Citations: 1.4W
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