2021
DOI: 10.3390/electronics10010067
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A Cartesian Genetic Programming Based Parallel Neuroevolutionary Model for Cloud Server’s CPU Usage Prediction

Abstract: Cloud computing use is exponentially increasing with the advent of industrial revolution 4.0 technologies such as the Internet of Things, artificial intelligence, and digital transformations. These technologies require cloud data centers to process massive volumes of workloads. As a result, the data centers consume gigantic amounts of electrical energy, and a large portion of data center electrical energy comes from fossil fuels. It causes greenhouse gas emissions and thus ensuing in global warming. An adaptiv… Show more

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Cited by 5 publications
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“…The advantage of NEAT is that it allows neural networks to evolve both their weights and topology, without having to heuristically specify the desired network topology. Neuroevolutionary algorithms for signal/data processing are being explored in several branches of applied sciences, such as materials science [30], gaming [31] and cloud computing [32].…”
Section: Literature Review and Motivationmentioning
confidence: 99%
“…The advantage of NEAT is that it allows neural networks to evolve both their weights and topology, without having to heuristically specify the desired network topology. Neuroevolutionary algorithms for signal/data processing are being explored in several branches of applied sciences, such as materials science [30], gaming [31] and cloud computing [32].…”
Section: Literature Review and Motivationmentioning
confidence: 99%