Workload Scheduling For Massive Storage Systems With Arbitrary Renewable Supply
Keywords
Renewable energy; SSD cache; storage system
Abstract
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.
Publication Date
10-1-2018
Publication Title
IEEE Transactions on Parallel and Distributed Systems
Volume
29
Issue
10
Number of Pages
2373-2387
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/TPDS.2018.2820070
Copyright Status
Unknown
Socpus ID
85044866478 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85044866478
STARS Citation
Li, Daping; Qu, Xiaoyang; Wan, Jiguang; Wang, Jun; and Xia, Yang, "Workload Scheduling For Massive Storage Systems With Arbitrary Renewable Supply" (2018). Scopus Export 2015-2019. 9201.
https://stars.library.ucf.edu/scopus2015/9201