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IaaS clouds invest substantial capital in operating their data centers.Reducing the cost of resource provisioning, is their forever pursuing goal.Computing resource trading among multiple IaaS clouds provide a potential forIaaS clouds to utilize cheaper resources to fulfill their jobs, by exploitingthe diversities of different clouds' workloads and operational costs. In thispaper, we focus on studying the IaaS clouds' cost reduction through computingresource trading among multiple IaaS clouds. We formulate the global costminimization problem among multiple IaaS clouds under cooperative scenariowhere each individual cloud's workload and cost information is known. Takinginto consideration jobs with disparate lengths, a non-preemptive approximationalgorithm for leftover job migration and new job scheduling is designed. Givento the selfishness of individual clouds, we further design a randomized doubleauction mechanism to elicit clouds' truthful bidding for buying or sellingvirtual machines. We evaluate our algorithms using trace-driven simulations.

Cost Minimization in Multiple IaaS Clouds: A Double Auction Approach