most capacity or leases a VM with most cost-performance ratio from the public cloud when there is no available PM in the local cloud, and assigns tasks to the cores of the added PM/VM as the previous step.

3.  We conduct extensive simulation experiments using two real work traces to investigate the effectiveness and efficiency of the proposed algorithm. The experiments results show that our heuristic algorithm saves 16.2%-76% cost for finishing jobs within their respective deadlines and improves 47.3%-182.8% resource utilizations, compared with first fit decreasing (FFD) algorithm.

The rest of the paper is organized as follows. Section \[management\] presents our model and the heuristic algorithm for solving the model. Section \[ERA\] evaluates our work. Section \[RW\] discusses related work and Section \[CFW\] concludes this paper.

Hybrid Cloud Management {#management}
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In a hybrid cloud, as shown in Fig. \[arch\], a task of jobs runs on a core of a PM on the local cloud/cluster or of a VM leased from the public cloud. In this paper, the objective is to cost-efficiently provision resources to tasks and assign the tasks to the resources to meet the complete time within corresponding deadline in the hybrid cloud environment, i.e., to provide 