Cloud Infrastructure Estimation and Auto-Scaling Using Recurrent Cartesian Genetic Programming-Based ANN
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- @Article{Ullah:2020:ACC,
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author = "Qazi Zia Ullah and Gul Muhammad Khan and
Shahzad Hassan",
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journal = "IEEE Access",
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title = "Cloud Infrastructure Estimation and Auto-Scaling Using
Recurrent Cartesian Genetic Programming-Based ANN",
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year = "2020",
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volume = "8",
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pages = "17965--17985",
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keywords = "genetic algorithms, genetic programming, Cartesian
Genetic Programming, ANN",
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DOI = "doi:10.1109/ACCESS.2020.2966678",
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ISSN = "2169-3536",
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abstract = "Use of cloud resources has increased with the
increasing trend of organizations and governments
towards cloud adaptation. This increase in cloud
resource usage, leads to enormous amounts of energy
consumption by cloud data center servers. Energy can be
conserved in a cloud server by demand-based scaling of
resources. But reactive scaling may lead to excessive
scaling. That, in turn, results in enormous energy
consumption by useless scale up and scale down. The
scaling granularity can also result in excessive
scaling of the resource. Without a proper mechanism for
estimating cloud resource usage may lead to significant
scaling overheads. To overcome, such inefficiencies, we
present Cartesian genetic programming based neural
network for resource estimation and a rule-based
scaling system for IaaS cloud server. Our system
consists of a resource monitor, a resource estimator
and a scaling mechanism. The resource monitor takes
resource usage and feeds to the estimator for efficient
estimation of resources. The scaling system uses the
resource estimator's output for scaling the resource
with the granularity of a CPU core. The proposed method
has been trained and tested with real traces of
Bitbrains data center, producing promising results in
real-time. It has shown better prediction accuracy and
energy efficiency than predictive scaling systems from
literature.",
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notes = "Also known as \cite{8960529}",
- }
Genetic Programming entries for
Qazi Zia Ullah
Gul Muhammad Khan
Shahzad Hassan
Citations