Pricing model for revenue generation using Recurrent Neural Network for Cloud service provider

Meetu Kandpal, Kalyani Patel
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引用次数: 1

Abstract

Success of any product may depend on the price of product. Demand of a product is one of the factors to be considered for deriving price of the product. As many IT companies have started to move towards the cloud computing and cloud resources are delivered as product over internet. There are many companies providing cloud services like salesforce.com, Amazon AWS, Microsoft azure etc. Different cloud service providers have different pricing policies to enhance the revenue and user satisfaction. The cloud providers have pricing schemes for cloud resources under fixed pricing and dynamic pricing. Some of them favor cloud providers, other cloud consumers. The paper presents a model to predict the price of cloud resource using Recurrent Neural Network(RNN) and auctioning method based on the parameters (as demand). The paper would give insight to researchers and cloud service providers to derive the policies based on the demand and other features.
云服务提供商使用递归神经网络生成收益的定价模型
任何产品的成功都可能取决于产品的价格。产品的需求是推导产品价格时要考虑的因素之一。随着许多IT公司开始转向云计算,云资源作为产品通过互联网交付。有许多公司提供云服务,如salesforce.com、亚马逊AWS、微软azure等。不同的云服务提供商有不同的定价策略,以提高收入和用户满意度。云提供商对云资源有固定定价和动态定价两种定价方案。其中一些支持云提供商,另一些支持云消费者。提出了一种基于参数(按需)的云资源价格预测模型,采用递归神经网络(RNN)和拍卖方法进行预测。本文将为研究人员和云服务提供商提供基于需求和其他特征的策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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