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https://doi.org/10.1109/icpads...
Article . 2012 . Peer-reviewed
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https://dx.doi.org/10.48550/ar...
Article . 2012
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An Optimal Fully Distributed Algorithm to Minimize the Resource Consumption of Cloud Applications

Authors: Nikos Tziritas; Samee Ullah Khan; Cheng-Zhong Xu 0001; Jue Hong;

An Optimal Fully Distributed Algorithm to Minimize the Resource Consumption of Cloud Applications

Abstract

According to the pay-per-use model adopted in clouds, the more the resources consumed by an application running in a cloud computing environment, the greater the amount of money the owner of the corresponding application will be charged. Therefore, applying intelligent solutions to minimize the resource consumption is of great importance. Because centralized solutions are deemed unsuitable for large-distributed systems or large-scale applications, we propose a fully distributed algorithm (called DRA) to overcome the scalability issues. Specifically, DRA migrates the inter-communicating components of an application, such as processes or virtual machines, close to each other to minimize the total resource consumption. The migration decisions are made in a dynamic way and based only on local information. We prove that DRA achieves convergence and results always in the optimal solution.

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Keywords

FOS: Computer and information sciences, Computer Science - Distributed, Parallel, and Cluster Computing, Distributed, Parallel, and Cluster Computing (cs.DC)

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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!
10
Top 10%
Top 10%
Average
Green