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

Abstract

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.