Reducing energy bill of data center via flexible partial execution
Several Demand Response (DR) strategies are emerged recently to modulate the workloads of Data Center (DC) and shave the corresponding energy bill. However, since most of these DR strategies will result in the increase of latency, they can only be used for modulating the elastic workloads, which are...
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| Format: | Article |
| Language: | English English |
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Springer
2018
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| Online Access: | http://umpir.ump.edu.my/id/eprint/30347/1/Reducing%20energy%20bill%20of%20data%20center%20via%20flexible%20partial%20execution_FULL.pdf http://umpir.ump.edu.my/id/eprint/30347/2/Reducing%20energy%20bill%20of%20data%20center%20via%20flexible%20partial%20execution.pdf |
| _version_ | 1796994411554406400 |
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| author | Shubin, Wang Xinni, Liu Shen, Jiang Yong, Zhan |
| author_facet | Shubin, Wang Xinni, Liu Shen, Jiang Yong, Zhan |
| author_sort | Shubin, Wang |
| collection | UMP |
| description | Several Demand Response (DR) strategies are emerged recently to modulate the workloads of Data Center (DC) and shave the corresponding energy bill. However, since most of these DR strategies will result in the increase of latency, they can only be used for modulating the elastic workloads, which are delay-tolerant. To improve the flexibility of workload modulation and reduction of energy bill, we propose flexible partial execution for DC, which can be used to handle inelastic workloads. Further, to incentivize users of DC grant flexible partial execution of their workloads, we offer them time-varying price discount, on top of commonly-applied usage-based pricing policy. With real-world data traces, the results show that a DC with our proposed flexible partial execution can shave its peak power consumption and energy bill by 30.9%30.9% and 20.8%20.8% while improving its profit by 18.8%18.8% when comparing against the one with rigid partial execution, i.e., a fixed percentage of requests/workloads can be partially executed, which is commonly employed by today’s DCs. |
| first_indexed | 2024-03-06T12:47:25Z |
| format | Article |
| id | UMPir30347 |
| institution | Universiti Malaysia Pahang |
| language | English English |
| last_indexed | 2024-03-06T12:47:25Z |
| publishDate | 2018 |
| publisher | Springer |
| record_format | dspace |
| spelling | UMPir303472021-01-06T03:46:28Z http://umpir.ump.edu.my/id/eprint/30347/ Reducing energy bill of data center via flexible partial execution Shubin, Wang Xinni, Liu Shen, Jiang Yong, Zhan TK Electrical engineering. Electronics Nuclear engineering Several Demand Response (DR) strategies are emerged recently to modulate the workloads of Data Center (DC) and shave the corresponding energy bill. However, since most of these DR strategies will result in the increase of latency, they can only be used for modulating the elastic workloads, which are delay-tolerant. To improve the flexibility of workload modulation and reduction of energy bill, we propose flexible partial execution for DC, which can be used to handle inelastic workloads. Further, to incentivize users of DC grant flexible partial execution of their workloads, we offer them time-varying price discount, on top of commonly-applied usage-based pricing policy. With real-world data traces, the results show that a DC with our proposed flexible partial execution can shave its peak power consumption and energy bill by 30.9%30.9% and 20.8%20.8% while improving its profit by 18.8%18.8% when comparing against the one with rigid partial execution, i.e., a fixed percentage of requests/workloads can be partially executed, which is commonly employed by today’s DCs. Springer 2018-12-15 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/30347/1/Reducing%20energy%20bill%20of%20data%20center%20via%20flexible%20partial%20execution_FULL.pdf pdf en http://umpir.ump.edu.my/id/eprint/30347/2/Reducing%20energy%20bill%20of%20data%20center%20via%20flexible%20partial%20execution.pdf Shubin, Wang and Xinni, Liu and Shen, Jiang and Yong, Zhan (2018) Reducing energy bill of data center via flexible partial execution. Journal of Ambient Intelligence and Humanized Computing. pp. 1-9. ISSN 1868-5137. (Published) https://doi.org/10.1007/s12652-018-1157-9 https://doi.org/10.1007/s12652-018-1157-9 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Shubin, Wang Xinni, Liu Shen, Jiang Yong, Zhan Reducing energy bill of data center via flexible partial execution |
| title | Reducing energy bill of data center via flexible partial execution |
| title_full | Reducing energy bill of data center via flexible partial execution |
| title_fullStr | Reducing energy bill of data center via flexible partial execution |
| title_full_unstemmed | Reducing energy bill of data center via flexible partial execution |
| title_short | Reducing energy bill of data center via flexible partial execution |
| title_sort | reducing energy bill of data center via flexible partial execution |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/30347/1/Reducing%20energy%20bill%20of%20data%20center%20via%20flexible%20partial%20execution_FULL.pdf http://umpir.ump.edu.my/id/eprint/30347/2/Reducing%20energy%20bill%20of%20data%20center%20via%20flexible%20partial%20execution.pdf |
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