as more resources required for processing more tasks and that HA saves 25.7%-58.1% costs compared with FFD.

These results above indicate that both HA and FFD have good scalability and that HA is better than FFD in minimizing rent cost.

Related Work {#RW}
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Outsourcing jobs to a public cloud is a cost-effective way to address the problem of satisfying the peak resource demand when the local cloud/cluster has insufficient resources. There are various researches on scheduling scientific applications on hybrid clouds.

To minimize the cost for leased resources from public clouds, W. Z. Jiang and Z. Q. sheng [@CSC] modelled the mapping of tasks and VMs as a bipartite graph. The two independent vertex sets of the bipartite graph are task and VM collections, respectively. The weight of an edge is the VM cost of a discrete task, i.e. the product of the running time of the task and the cost of the VM per unit time. Then the problem minimizing the cost is to find a subset of the edge set, where the weighted sum of all the edges in the subset is the minimum. The authors used the Hopcroft-Karp algorithm [@HKA] to solve the minimum bipartite match 