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https://doi.org/10.1109/nca.20...
Article . 2012 . Peer-reviewed
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Greening the Internet: Energy-Optimal File Distribution

Authors: Kshitiz Verma; Gianluca Rizzo; Antonio Fernández Anta; Rubén Cuevas Rumín; Arturo Azcorra;

Greening the Internet: Energy-Optimal File Distribution

Abstract

Despite file distribution applications are responsible for a major portion of the current Internet traffic, so far little effort has been dedicated to study file distribution from the point of view of energy efficiency. In this paper, we present the first extensive and detailed theoretical study for the problem of energy efficiency in file distribution. Specifically, we first demonstrate that the general problem of minimizing energy consumption in file distribution is NP-hard. For restricted versions of the problem, we derive tight lower bounds on energy consumption, and we design a family of algorithms that achieve these bounds. Our results prove that through collaborative p2p schemes up to 50% energy savings are achievable with respect to the best available centralized file distribution scheme. Through simulation, we show that even in heterogeneous settings (e.g., considering network congestion, and link variability across hosts) our collaborative algorithms always achieve significant energy savings with respect to the power consumption of centralized file distribution systems.

TRUE

pub

Countries
Spain, Italy
Keywords

:QA Mathematics::QA75 Electronic computers. Computer science [Q Science], Q Science::QA Mathematics::QA75 Electronic computers. Computer science, :T Technology (General) [T Technology], Q Science::Q Science (General), T Technology::TA Engineering (General). Civil engineering (General), T Technology::TK Electrical engineering. Electronics Nuclear engineering, T Technology::T Technology (General), Energy efficiency, file distribution, :Q Science (General) [Q Science], :TK Electrical engineering. Electronics Nuclear engineering [T Technology], theory, Algorithms, :TA Engineering (General). Civil engineering (General) [T Technology]

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selected citations
These citations are derived from selected sources.
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!
2
Average
Average
Average
Green
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