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Conference object . 2017
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https://doi.org/10.1109/cdc.20...
Article . 2017 . Peer-reviewed
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Conference object . 2018
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Controlling G-AIMD by index policy

Authors: Avrachenkov, Konstantin; Borkar, Vivek; Pattathil, Sarath;

Controlling G-AIMD by index policy

Abstract

We consider the Generalized Additive Increase Multiplicative Decrease (G-AIMD) dynamics for resource allocation with alpha fairness utility function. This dynamics has a number of important applications such as internet congestion control, charging electric vehicles, and smart grids. We prove indexability for the special case of MIMD model and provide an efficient scheme to compute the index. The use of index policy allows us to avoid the curse of dimensionality. We also demonstrate through simulations for another special case, AIMD, that the index policy is close to optimal and significantly outperforms a natural heuristic which penalizes the strongest user.

Country
France
Keywords

[INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI], [MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]

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    popularity
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    influence
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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!
4
Average
Average
Average
Green