research-article

Lightning: self-adaptive, energy-conserving, multi-zoned, commodity green cloud storage system

Authors:

Rini T. Kaushik,

Ludmila Cherkasova,

Roy Campbell,

Klara NahrstedtAuthors Info & Claims

HPDC '10: Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing

Pages 332 - 335

https://doi.org/10.1145/1851476.1851523

Published: 21 June 2010 Publication History

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Abstract

The objective of this research is to present an energy-conserving, self-adaptive Commodity Green Cloud Storage, called Lightning. Lightning's File System dynamically configures the servers in the Cloud Storage into logical Hot and Cold Zones. Lightning uses data-classification driven data placement to realize guaranteed, substantially long, periods (several days) of idleness in a significant subset of servers designated as the Cold Zone, in the commodity datacenter backing the Cloud Storage. These servers are then transitioned to inactive power modes and the resulting energy savings substantially reduce the operating costs of the datacenter. Furthermore, the energy savings allow Lightning to improve the data access performance by incorporation of high-performance, though high-cost Solid State Drives (SSD) without exceeding the total cost of ownership (TCO) of the datacenter. Analytical cost model analysis of Lightning suggests savings in the upwards of $24 million in the TCO of a 20,000 server datacenter. The simulation results show that Lightning can achieve 46% energy costs reduction even when the datacenter is at 80% capacity utilization.

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Yuan ZLv XGong YLiu BYang HYou X(2024)Text Semantics-Driven Data Classification Storage OptimizationApplied Sciences10.3390/app1403115914:3(1159)Online publication date: 30-Jan-2024
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Li JDeng YWang RZhou YFeng HMin GQin X(2024)BTVMP: A Burst-Aware and Thermal-Efficient Virtual Machine Placement Approach for Cloud Data CentersIEEE Transactions on Services Computing10.1109/TSC.2023.333826717:5(2080-2094)Online publication date: Sep-2024
https://doi.org/10.1109/TSC.2023.3338267
Yuan ZLv XGong YXie PYuan TYou X(2024)Cost-effective data classification storage through text seasonal featuresFuture Generation Computer Systems10.1016/j.future.2024.04.061158(472-487)Online publication date: Sep-2024
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Index Terms

Lightning: self-adaptive, energy-conserving, multi-zoned, commodity green cloud storage system
1. Information systems
  1. Information storage systems
    1. Storage management
2. Software and its engineering
  1. Software organization and properties
    1. Contextual software domains
      1. Operating systems
        File systems management
        Memory management

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Published In

HPDC '10: Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing

June 2010

911 pages

ISBN:9781605589428

DOI:10.1145/1851476

General Chairs:
Salim Hariri
University of Arizona
,
Kate Keahey
University of Chicago

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 June 2010

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HPDC '10

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University of Arizona
SIGARCH

HPDC '10: The 19th International Symposium on High Performance Distributed Computing

June 21 - 25, 2010

Illinois, Chicago

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Overall Acceptance Rate 166 of 966 submissions, 17%

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Cited By

View all

Yuan ZLv XGong YLiu BYang HYou X(2024)Text Semantics-Driven Data Classification Storage OptimizationApplied Sciences10.3390/app1403115914:3(1159)Online publication date: 30-Jan-2024
https://doi.org/10.3390/app14031159
Li JDeng YWang RZhou YFeng HMin GQin X(2024)BTVMP: A Burst-Aware and Thermal-Efficient Virtual Machine Placement Approach for Cloud Data CentersIEEE Transactions on Services Computing10.1109/TSC.2023.333826717:5(2080-2094)Online publication date: Sep-2024
https://doi.org/10.1109/TSC.2023.3338267
Yuan ZLv XGong YXie PYuan TYou X(2024)Cost-effective data classification storage through text seasonal featuresFuture Generation Computer Systems10.1016/j.future.2024.04.061158(472-487)Online publication date: Sep-2024
https://doi.org/10.1016/j.future.2024.04.061
Machida FHasebe KAbe HKato K(2022)Analysis of Optimal File Placement for Energy-Efficient File-Sharing Cloud Storage SystemIEEE Transactions on Sustainable Computing10.1109/TSUSC.2020.30372607:1(75-86)Online publication date: 1-Jan-2022
https://doi.org/10.1109/TSUSC.2020.3037260
Yuan ZLv XXie PGe HYou X(2022)CSEA: A Fine-Grained Framework of Climate-Season-Based Energy-Aware in Cloud Storage SystemsThe Computer Journal10.1093/comjnl/bxac184Online publication date: 30-Dec-2022
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Wen ZGarg SAujla GAlwasel KPuthal DDustdar SZomaya ARanjan R(2021)Running Industrial Workflow Applications in a Software-Defined Multicloud Environment Using Green Energy Aware Scheduling AlgorithmIEEE Transactions on Industrial Informatics10.1109/TII.2020.304569017:8(5645-5656)Online publication date: Aug-2021
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Hu CDeng YMin GHuang PQin X(2021)QoS Promotion in Energy-Efficient Datacenters Through Peak Load SchedulingIEEE Transactions on Cloud Computing10.1109/TCC.2018.28861879:2(777-792)Online publication date: 1-Apr-2021
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You XLv XZhao ZHan JRen X(2020)A Survey and Taxonomy on Energy-Aware Data Management Strategies in Cloud EnvironmentIEEE Access10.1109/ACCESS.2020.29927488(94279-94293)Online publication date: 2020
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You XSun TSun DLiu XLv XBuyya R(2020)K‐ear: Extracting data access periodic characteristics for energy‐aware data clustering and storing in cloud storage systemsConcurrency and Computation: Practice and Experience10.1002/cpe.609633:9Online publication date: 30-Nov-2020
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K. IM. T(2018)Green Cloud ComputingCloud Computing Technologies for Green Enterprises10.4018/978-1-5225-3038-1.ch005(114-136)Online publication date: 2018
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