Paper Info
Title
Techniques for Efficiently Handling Power Surges in Fuel Cell Powered Data Centers: Modeling, Analysis, Results.
Abstract
Fuel cells are a promising power source for future data centers, offering high energy efficiency, low greenhouse gas emissions, and high reliability. However, due to mechanical limitations related to fuel delivery, fuel cells are slow to adjust to sudden increases in data center power demands, which can result in temporary power shortfalls. To mitigate the impact of power shortfalls, prior work has proposed to either perform power capping by throttling the servers, or to leverage energy storage devices (ESDs) that can temporarily provide enough power to make up for the shortfall while the fuel cells ramp up power generation. Both approaches have disadvantages: power capping conservatively limits server performance and can lead to service level agreement (SLA) violations, while ESD-only solutions must significantly overprovision the energy storage device capacity to tolerate the shortfalls caused by the worst-case (i.e., largest) power surges, which greatly increases the total cost of ownership (TCO). We propose SizeCap, the first ESD sizing framework for fuel cell powered data centers, which coordinates ESD sizing with power capping to enable a cost-effective solution to power shortfalls in data centers. SizeCap sizes the ESD just large enough to cover the majority of power surges, but not the worst-case surges that occur infrequently, to greatly reduce TCO. It then uses the smaller capacity ESD in conjunction with power capping to cover the power shortfalls caused by the worst-case power surges. As part of our new flexible framework, we propose multiple power capping policies with different degrees of awareness of fuel cell and workload behavior, and evaluate their impact on workload performance and ESD size. Using traces from Microsoftu0027s production data center systems, we demonstrate that SizeCap significantly reduces the ESD size without violating any SLAs.
Year
Venue
Field
2018
arXiv: Distributed, Parallel, and Cluster Computing
Energy storage,Computer science,Total cost of ownership,Server,Service-level agreement,Sizing,Data center,Bandwidth throttling,Reliability engineering,Electricity generation,Distributed computing
DocType
Volume
Citations 
Journal
abs/1806.04506
0
PageRank 
References 
Authors
0.34
11
10
Name
Order
Citations
PageRank
Yang Li160.75
Di Wang2127.09
Saugata Ghose371836.45
Jie Liu4143894.17
Sriram Govindan580738.92
Sean James6171.80
Eric Peterson760.80
John Siegler800.34
Rachata Ausavarungnirun978029.88
Onur Mutlu109446357.40