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Cloud providers offer end-users various pricing schemes to allow them totailor VMs to their needs, e.g., a pay-as-you-go billing scheme, called\textit{on-demand}, and a discounted contract scheme, called \textit{reservedinstances}. This paper presents a cloud broker which offers users both theflexibility of on-demand instances and some level of discounts found inreserved instances. The broker employs a buy-low-and-sell-high strategy thatplaces user requests into a resource pool of pre-purchased discounted cloudresources. By analysing user request time-series data, the broker takes arisk-oriented approach to dynamically adjust the resource pool.  This approach does not require a training process which is useful atprocessing the large data stream. The broker is evaluated with high-frequencyreal cloud datasets from Alibaba. The results show that the overall profit ofthe broker is close to the theoretical optimal scenario where user requests canbe perfectly predicted.

A Risk-taking Broker Model to Optimise User Requests placement on On-demand and Contract VMs