More Web Proxy on the site http://driver.im/

extended-abstract

Energy Consumption of Content Distribution from Nano Data Centers versus Centralized Data Centers

Authors:

Fatemeh Jalali,

Arun Vishwanath,

Rod TuckerAuthors Info & Claims

ACM SIGMETRICS Performance Evaluation Review, Volume 42, Issue 3

Pages 49 - 54

https://doi.org/10.1145/2695533.2695555

Published: 08 December 2014 Publication History

Abstract

Energy consumption of nano data centers has recently been a topic of interest as they emerge as a novel computing and storage platform. We present end-to-end energy consumption models for nano data centers and its centralized counterpart. To assess the energy consumption of nano and centralized data centers, we propose flowbased and time-based energy consumption models for shared and single user network equipment. To evaluate our models, a set of measurements and practical experiments are performed. Our results indicate that nano data centers might lead to energy savings depending on various factors such as location of nano servers, type of access network attached to nano servers, and the ratio of active time to idle time of nano servers. Thus, nano data centers can complement centralized ones and lead to savings energy if certain applications are off-loadable from centralized data centers.

References

[1]

Amn1220 optical line terminal (olt) - data sheet.

[2]

Cisco global cloud index: Forecast and methodology, 2012-2017.

[3]

Code of conduct on energy consumption of broadband equipment, version 4.1.

[4]

The power of wireless cloud: An analysis of the impact on energy consumption of the growing popularity of accessing cloud services via wireless devices.

[5]

Powermate - a power meter.

[6]

Raspberry pi - a credit-card-sized single-board computer.

[7]

Wordpress - website and blogging tool.

[8]

J. Baliga, R. Ayre, K. Hinton, and R. Tucker. Architectures for energy-efficient iptv networks. In Optical Fiber Communication - incudes post deadline papers, 2009. OFC 2009. Conference on, pages 1--3, March 2009.

[9]

J. Baliga, R. Ayre, K. Hinton, and R. Tucker. Green cloud computing: Balancing energy in processing, storage, and transport. Proceedings of the IEEE, 99(1):149--167, 2011.

[10]

C. A. Chan, E. Wong, A. Nirmalathas, A. F. Gygax, and C. Leckie. Energy efficiency of on-demand video caching systems and user behavior. Opt. Express, 19(26):B260--B269, Dec 2011.

[11]

A. Feldmann, A. Gladisch, M. Kind, C. Lange, G. Smaragdakis, and F. Westphal. Energy trade-offs among content delivery architectures. In Telecommunications Internet and Media Techno Economics (CTTE), 2010 9th Conference on, pages 1--6, 2010.

[12]

D. Fritz. The evolving wireless world. alcatel lucent presentation.

[13]

P. X. Gao, A. R. Curtis, B. Wong, and S. Keshav. It's not easy being green. SIGCOMM Comput. Commun. Rev., 42(4):211--222, Aug. 2012.

Digital Library

[14]

V. G. Gunther Auer, Oliver Blume. Energy efficiency analysis of the reference systems, areas of improvements and target breakdown (earth).

[15]

J. Hamilton. Overall data center costs.

[16]

J. Hamilton. Perspectives data center cost and power.

[17]

B. Heller, S. Seetharaman, P. Mahadevan, Y. Yiakoumis, P. Sharma, S. Banerjee, and N. McKeown. Elastictree: Saving energy in data center networks. In Proceedings of the 7th USENIX Conference on Networked Systems Design and Implementation, NSDI'10, pages 17--17, 2010.

Digital Library

[18]

U. Lee, I. Rimac, D. Kilper, and V. Hilt. Toward energy-efficient content dissemination. Network, IEEE, 25(2):14--19, March 2011.

Digital Library

[19]

U. Mandal, P. Chowdhury, C. Lange, A. Gladisch, and B. Mukherjee. Energy-efficient networking for content distribution over telecom network infrastructure. Optical Switching and Networking, 10(4):393--405, 2013.

[20]

D. Meisner, B. T. Gold, and T. F. Wenisch. Powernap: Eliminating server idle power. SIGARCH Comput. Archit. News, 37(1):205--216, Mar. 2009.

Digital Library

[21]

S. Nedevschi, S. Ratnasamy, and J. Padhye. Hot data centers vs. cool peers. In Proceedings of the 2008 conference on Power aware computing and systems, HotPower'08, pages 8--8, 2008.

Digital Library

[22]

V. Valancius, N. Laoutaris, L. Massoulié, C. Diot, and P. Rodriguez. Greening the internet with nano data centers. In Proceedings of the 5th international conference on Emerging networking experiments and technologies, CoNEXT '09, pages 37--48, 2009.

Digital Library

[23]

A. Vishwanath, F. Jalali, R. Ayre, T. Alpcan, K. Hinton, and R. Tucker. Energy consumption of interactive cloud-based document processing applications. In Communications (ICC), 2013 IEEE International Conference on, 2013.

[24]

A. Vishwanath, J. Zhu, K. Hinton, R. Ayre, and R. Tucker. Estimating the energy consumption for packet processing, storage and switching in optical-ip routers. page OM3A.6, 2013.

[25]

N. Xu, J. Yang, M. Needham, D. Boscovic, and F. Vakil. Toward the green video cdn. In Green Computing and Communications (GreenCom), 2010 IEEE/ACM Int'l Conference on Int'l Conference on Cyber, Physical and Social Computing (CPSCom), pages 430--435, 2010.

Digital Library

Cited By

Woisetschläger HErben AMayer RWang SJacobsen HSchiavoni VEdinger JCao JJin Z(2024)FLEdge: Benchmarking Federated Learning Applications in Edge Computing SystemsProceedings of the 25th International Middleware Conference10.1145/3652892.3700751(88-102)Online publication date: 2-Dec-2024
https://dl.acm.org/doi/10.1145/3652892.3700751
Woisetschläger HErben AWang SMayer RJacobsen H(2024)Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the UglyProceedings of the Eighth Workshop on Data Management for End-to-End Machine Learning10.1145/3650203.3663331(39-50)Online publication date: 9-Jun-2024
https://dl.acm.org/doi/10.1145/3650203.3663331
Perez-Valero JBanchs ASerrano POrtín JGarcia-Reinoso JCosta-Pérez X(2024)Energy-Aware Adaptive Scaling of Server Farms for NFV with Reliability RequirementsIEEE Transactions on Mobile Computing10.1109/TMC.2023.3288604(1-13)Online publication date: 2024
https://doi.org/10.1109/TMC.2023.3288604
Show More Cited By

Energy Consumption of Content Distribution from Nano Data Centers versus Centralized Data Centers

Recommendations

Greening the internet with nano data centers
CoNEXT '09: Proceedings of the 5th international conference on Emerging networking experiments and technologies

Motivated by increased concern over energy consumption in modern data centers, we propose a new, distributed computing platform called Nano Data Centers (NaDa). NaDa uses ISP-controlled home gateways to provide computing and storage services and adopts ...
On energy consumption of switch-centric data center networks

Data center network (DCN) is the core of cloud computing and accounts for 40% energy spend when compared to cooling system, power distribution and conversion of the whole data center (DC) facility. It is essential to reduce the energy consumption of DCN ...
Energy Consumption of IT System in Cloud Data Center: Architecture, Factors and Prediction
Network and Parallel Computing
Abstract
In recent years, as cloud data center has grown constantly in size and quantity, the energy consumption of cloud data center has increased dramatically. Therefore, it is of great significance to study the energy-saving issues of cloud data centers ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM SIGMETRICS Performance Evaluation Review

ACM SIGMETRICS Performance Evaluation Review Volume 42, Issue 3

December 2014

80 pages

ISSN:0163-5999

DOI:10.1145/2695533

Editor:
Giuliano Casale
Imperial College London, London

Issue’s Table of Contents

Copyright © 2014 Authors.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 December 2014

Published in SIGMETRICS Volume 42, Issue 3

Check for updates

Author Tags

Qualifiers

Extended-abstract

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

10
Total Citations
View Citations
260
Total Downloads

Downloads (Last 12 months)17
Downloads (Last 6 weeks)1

Reflects downloads up to 17 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Woisetschläger HErben AMayer RWang SJacobsen HSchiavoni VEdinger JCao JJin Z(2024)FLEdge: Benchmarking Federated Learning Applications in Edge Computing SystemsProceedings of the 25th International Middleware Conference10.1145/3652892.3700751(88-102)Online publication date: 2-Dec-2024
https://dl.acm.org/doi/10.1145/3652892.3700751
Woisetschläger HErben AWang SMayer RJacobsen H(2024)Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the UglyProceedings of the Eighth Workshop on Data Management for End-to-End Machine Learning10.1145/3650203.3663331(39-50)Online publication date: 9-Jun-2024
https://dl.acm.org/doi/10.1145/3650203.3663331
Perez-Valero JBanchs ASerrano POrtín JGarcia-Reinoso JCosta-Pérez X(2024)Energy-Aware Adaptive Scaling of Server Farms for NFV with Reliability RequirementsIEEE Transactions on Mobile Computing10.1109/TMC.2023.3288604(1-13)Online publication date: 2024
https://doi.org/10.1109/TMC.2023.3288604
Jaiswal RDavidrajuh RWondimagegnehu SDavidrajuh ROwolawi P(2021)Fog Computing for Efficient Predictive Analysis in Smart GridsProceedings of the International Conference on Artificial Intelligence and its Applications10.1145/3487923.3487937(1-6)Online publication date: 9-Dec-2021
https://dl.acm.org/doi/10.1145/3487923.3487937
Kumar DBaranwal GVidyarthi D(2021)A Survey on Auction based Approaches for Resource Allocation and Pricing in Emerging Edge TechnologiesJournal of Grid Computing10.1007/s10723-021-09593-920:1Online publication date: 27-Dec-2021
https://doi.org/10.1007/s10723-021-09593-9
Hameed Mohsin AAl Omary A(2020)Security and Power Management in IoT and Fog Computing: A Survey2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI)10.1109/ICDABI51230.2020.9325653(1-6)Online publication date: 26-Oct-2020
https://doi.org/10.1109/ICDABI51230.2020.9325653
Behbehani FMusa MElgorashi TElmirghani J(2019)Energy Efficient Distributed Processing in Vehicular Cloud Architecture2019 21st International Conference on Transparent Optical Networks (ICTON)10.1109/ICTON.2019.8840335(1-4)Online publication date: Jul-2019
https://doi.org/10.1109/ICTON.2019.8840335
Li CXue YWang JZhang WLi T(2018)Edge-Oriented Computing ParadigmsACM Computing Surveys10.1145/315481551:2(1-34)Online publication date: 17-Apr-2018
https://dl.acm.org/doi/10.1145/3154815
Jalali FVishwanath Ade Hoog JSuits F(2016)Interconnecting Fog computing and microgrids for greening IoT2016 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia)10.1109/ISGT-Asia.2016.7796469(693-698)Online publication date: Nov-2016
https://doi.org/10.1109/ISGT-Asia.2016.7796469
Cuadrado-Cordero IOrgerie AMorin C(2015)GRaNADAProceedings of the 2015 IEEE International Conference on Data Science and Data Intensive Systems (DSDIS)10.1109/DSDIS.2015.65(412-419)Online publication date: 11-Dec-2015
https://dl.acm.org/doi/10.1109/DSDIS.2015.65

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Issue’s Table of Contents