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An efficient resource deployment method for stream-based stochastic demands in distributed cloud platforms

机译:分布式云平台中基于流的随机需求的高效资源部署方法

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摘要

It has been a consensus that deploying geographically dispersed stream-based online services into distributed cloud platforms has gained exceptional advantages. Globally visiting services make user requests characterised with dramatic fluctuation, which introduces stochastic demands for various resources. In order to maximise satisfied user requests and guarantee quality-of-service under given expense budget, efficient resource deployment becomes the key to this problem. We propose a stochastic demand oriented resource deployment method with more profits and less time complexity. Experiments using simulated and realistic data indicate that proposed method can outperform existing algorithms by increasing the weighted summation of satisfied demands up to 37%, fit for all scenarios with heterogeneous distributed cloud resources.
机译:它已达成共识,即将基于地理分散的流的在线服务部署到分布式云平台上取得了卓越的优势。全球访问服务使用户请求具有戏剧性波动,这引入了各种资源的随机需求。为了最大化满足用户请求并保证在给定的费用预算下的服务质量,有效的资源部署将成为此问题的关键。我们提出了一种随机需求导向的资源部署方法,具有更多利润和更少的时间复杂性。使用模拟和现实数据的实验表明,所提出的方法可以通过将满足要求的加权总和增加到37%的加权总和,适用于具有异构分布式云资源的所有场景来优于现有算法。

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