Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao IEEE Transactions on...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
IEEE Transactions on Green Communications and Networking
Article . 2019 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
versions View all 2 versions
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Joint Workload Scheduling and Energy Management for Green Data Centers Powered by Fuel Cells

Authors: Xiaoxuan Hu; Peng Li; Kun Wang; Yanfei Sun; Deze Zeng; Xiaoyan Wang; Song Guo;

Joint Workload Scheduling and Energy Management for Green Data Centers Powered by Fuel Cells

Abstract

The fuel cell is a promising power source for green data centers due to its high energy efficiency, low carbon emissions, and high reliability. However, because of the mechanical limitations related to fuel delivery, fuel cells are slow in adjusting power output when the energy demand quickly changes, which is called limited load following . Many recent work have studied to mitigate the limited load following by using energy storage to adjust energy supply, but achieves limited successes because of the constraint of energy storage size. In this paper, we address this challenge by changing both energy supply and demand, via joint workload scheduling and energy management. Specifically, we consider multiple geo-distributed data centers powered by both fuel cells and energy storage. An online algorithm has been proposed to minimize the gap between energy supply and demand by jointly managing the fuel cells output and migrating workloads among data centers. Simulations results based on real-world traces show that the proposed algorithms can achieve satisfactory performance.

Country
China (People's Republic of)
Keywords

690, Job scheduling, Fuel cell, Cost minimization, 600, Data center, Lyapunov optimization

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    12
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Top 10%
Average
Top 10%