Cloud is an increasingly popular computing paradigm that provides on-demand services to organizations for deploying their business processes over the Internet as it reduces their needs to plan ahead for provisioning resources. Cloud providers offer competitive pricing strategies (e.g., on-demand, reserved, and spot) specified based on temporal constraints to accommodate organizations’ changing and last-minute demands. Despite their varieties and benefits to optimize business process deployment cost, using those pricing strategies can lead to violating time constraints and exceeding budget constraints due to inappropriate decisions when allocating cloud resources to business processes. In this paper, we present an approach to guarantee a correct and optimal time-aware allocation of cloud resources to business processes. Correct because time constraints on these processes are not violated. And, optimal because the deployment cost of these processes is minimized. For this purpose, our approach uses timed automata to formally verify the matching between business processes’ temporal constraints and cloud resources’ time availabilities and linear programming to optimize deployment costs. Experiments demonstrate the technical doability of our proposed approach.

云是一种越来越流行的计算范例，它为组织提供按需服务，以通过Internet部署其业务流程，因为它减少了他们提前计划供应资源的需求。云提供商根据时间限制提供有竞争力的定价策略（例如，按需，预留和现货），以适应组织不断变化的需求和最新需求。尽管它们具有优化业务流程部署成本的多样性和优势，但在将云资源分配给业务流程时，使用这些定价策略可能会导致违反时间限制并超出预算限制，原因是决策不当。在本文中，我们提出一种方法，以确保正确，最佳地将时间感知的云资源分配给业务流程。正确，因为没有违反这些过程的时间限制。并且，因为这些过程的部署成本已最小化，所以是最佳的。为此，我们的方法使用定时自动机来正式验证业务流程的时间约束与云资源的时间可用性之间的匹配，并通过线性编程来优化部署成本。实验证明了我们提出的方法的技术可行性。