Cloud computing is a rapidly growing paradigm in software engineering that offers different services. The hybrid cloud is the best choice for the enterprise to benefit by taking resources on lease from the public cloud only if private cloud resources are not sufficient. However, the key is how to provide better cloud services and improve software performance in the hybrid cloud for software engineers. In this paper, the efficient job scheduling method in the private cloud is proposed by considering the heterogeneity of hybrid cloud resources to guarantee the software performance and reliability. The experimental results show that the efficient job scheduling method can effectively reduce the average job response time and improve the system throughput. Moreover, the task scheduling method based on BP neural network in the hybrid cloud is proposed by considering both the cost and deadline constraints to ensure the quality of service (QoS) for software. The experimental results show that the task scheduling method can improve the QoS, maximize the resources utilization of private cloud and minimize the cost of hybrid cloud resources.

中文翻译：

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成本意识调度，确保混合云异构工作负载下的软件性能和可靠性

云计算是软件工程中快速发展的范例，可提供不同的服务。只有在私有云资源不足的情况下，混合云才是企业通过从公共云租用资源而受益的最佳选择。然而，关键是如何在混合云中为软件工程师提供更好的云服务和提高软件性能。本文通过考虑混合云资源的异构性，提出了私有云中高效的作业调度方法，以保证软件的性能和可靠性。实验结果表明，高效的作业调度方法能够有效降低平均作业响应时间，提高系统吞吐量。而且，提出了混合云中基于BP神经网络的任务调度方法，同时考虑成本和期限约束，以保证软件的服务质量(QoS)。实验结果表明，该任务调度方法能够提高服务质量，最大化私有云资源利用率，最小化混合云资源成本。