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Cloud computing delivers value to users by facilitating their access tocomputing capacity in periods when their need arises. An approach is to provideboth on-demand and spot services on shared servers. The former allows users toaccess servers on demand at a fixed price and users occupy different periods ofservers. The latter allows users to bid for the remaining unoccupied periodsvia dynamic pricing; however, without appropriate design, such periods may bearbitrarily small since on-demand users arrive randomly. This is also thecurrent service model adopted by Amazon Elastic Cloud Compute. In this paper,we provide the first integral framework for sharing the time of servers betweenon-demand and spot services while optimally pricing spot instances. Itguarantees that on-demand users can get served quickly while spot users canstably utilize servers for a properly long period once accepted, which is a keyfeature to make both on-demand and spot services accessible. Simulation resultsshow that, by complementing the on-demand market with a spot market, a cloudprovider can improve revenue by up to 464.7%. The framework is designed underassumptions which are met in real environments. It is a new tool that cloudoperators can use to quantify the advantage of a hybrid spot and on-demandservice, eventually making the case for operating such service model in theirown infrastructures.

A Framework for Allocating Server Time to Spot and On-demand Services in Cloud Computing