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Statistical analysis of Amazon EC2 cloud pricing models

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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A Declarative Recommender System for Cloud Infrastructure Services Selection

inferredcites →https://doi.org/10.1016/j.future.2012.06.012openalex-snapshot

Characterizing spot price dynamics in public cloud environments

inferredcites →https://doi.org/10.1016/j.jss.2015.10.042openalex-snapshot

Spot pricing in the Cloud ecosystem: A comparative investigation

inferredcites →https://doi.org/10.1109/cloud.2015.101openalex-snapshot

Automating Resource Selection and Configuration in Inter-clouds through a Software Product Line Method

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Dynamic Price Prediction for Amazon Spot Instances

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SpotLight: An Information Service for the Cloud

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Virtual Infrastructure Management in Private and Hybrid Clouds

inferredcites →https://doi.org/10.1109/mic.2014.87openalex-snapshot

Bidding Strategies for Spot Instances in Cloud Computing Markets

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Transient Guarantees: Maximizing the Value of Idle Cloud Capacity

inferredcites →https://doi.org/10.1145/2509413.2509416openalex-snapshot

Deconstructing Amazon EC2 Spot Instance Pricing

inferredcites →https://doi.org/10.14778/2850583.2850590openalex-snapshot

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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Energy-based Cost Model of Virtual Machines in a Cloud Environment

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How Can We Train Deep Learning Models Across Clouds and Continents? An Experimental Study

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Prediksi Indeks Harga Konsumen Komoditas Makanan Berbasis Cloud Computing Menggunakan Multilayer Perceptron

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AWS PredSpot: Machine Learning for Predicting the Price of Spot Instances in AWS Cloud.

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