Please wait a minute...
Shopping Cart Email List Chinese
Advanced Search Fig/Tab
Frontiers of Computer Science

ISSN 2095-2228

ISSN 2095-2236(Online)

CN 10-1014/TP

Postal Subscription Code 80-970

2018 Impact Factor: 1.129

Featured Articles  |  Most Downloaded  |  Most Reading
Online Submission Subscribe to Our RSS Content Feed
Front. Comput. Sci.    2025, Vol. 19 Issue (5) : 195108    https://doi.org/10.1007/s11704-024-40184-5
Architecture
FLAPS: fluctuation-aware power auction strategy for reducing the power overload probability
Xiaoqing CAI, Han ZHAO(), Xiaofeng HOU, Weihao CUI, Quan CHEN, Chao LI, Minyi GUO
Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
 Download: PDF(710 KB)   HTML
 Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Corresponding Author(s): Han ZHAO   
Just Accepted Date: 11 September 2024   Issue Date: 25 October 2024
 Cite this article:   
Minyi GUO,Chao LI,Quan CHEN, et al. FLAPS: fluctuation-aware power auction strategy for reducing the power overload probability[J]. Front. Comput. Sci., 2025, 19(5): 195108.
 URL:  
https://academic.hep.com.cn/fcs/EN/10.1007/s11704-024-40184-5
https://academic.hep.com.cn/fcs/EN/Y2025/V19/I5/195108
Fig.1  The problems with existing resource oversubscription techniques
Fig.2  Motivation for FLAPS. (a) shows the probability distribution of job power usage CV in both traces; (b) compares LSTM prediction results with actual resource usage
Fig.3  FLAPS framework overview
Fig.4  Structure of the prediction model
Fig.5  The bidding process
SchemeIdle power acquisitionAuction or allocation metric
Bid-RRealDemand
Bid-HHistoryDemand
DVFS-80RealPriority
DVFS-90RealPriority
FLAPSPredictDemand & deviation
FLAPS-HHistoryDemand & deviation
FLAPS-RRealDemand & deviation
Tab.1  Evaluated resource allocation schemes
Fig.6  The power overload ratio (a) and power usage utilization (b) of seven schemes
1 J Wilkes . Yet more Google compute cluster trace data. See Research.google/blog/yet-more-google-compute-cluster-trace-data/website, 2020
2 M A, Islam X, Ren S, Ren A Wierman . A spot capacity market to increase power infrastructure utilization in multi-tenant data centers. In: Proceedings of ACM SIGMETRICS/International Conference on Measurement and Modeling of Computer Systems. 2017, 19−20
3 L, Piga I, Narayanan A, Sundarrajan M, Skach Q, Deng B, Maity M, Chakkaravarthy A, Huang A, Dhanotia P Malani . Expanding datacenter capacity with DVFS boosting: a safe and scalable deployment experience. In: Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems. 2024, 150−165
4 Alibaba cluster trace program. Alibaba Inc. See Github.com/alibaba/clusterdata/blob/master/cluster-tracemicroarchitecture-v2022/README.md. 2022
5 S, Rivoire P, Ranganathan C Kozyrakis . A comparison of high-level full-system power models. In: Proceedings of the 8th Workshop on Power Aware Computing and Systems. 2008, 32−39
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed