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Cost optimization of business processes based on time constraints on cloud resources

Abstract : Motivated by the need of "optimizing the deployment cost of business processes" organizations outsource some of their operations to cloud computing. Cloud providers offer competitive pricing strategies (e.g., on-demand, reserved, and spot) specified based on temporal constraints to accommodate users' changing and last-minute demands. Besides, the organizations' business processes are time constrained and any violation to these constraints could lead to serious consequences. Therefore, there is a need to formally verify that the cloud resource allocation in a business process is temporally correct. However, due to the lack of a formal definition of cloud pricing strategies, specified in natural language, the temporal correctness of cloud resource allocation in a business process management context can not be verified. Furthermore, the variety of cloud resources, pricing strategies, and activities requirements do not help the business process designer to easily find the optimal business process's deployment cost. In this thesis, our objectives are to: (i) improve the business processes support of temporal constraints on activities and cloud resources, as well as pricing strategies and (ii) minimize the business process deployment cost. To this end, we propose a formal specification for cloud resources, pricing strategies, and activities' temporal constraints. This specification is used to formally verify the temporal correctness of cloud resource allocation in time-aware business processes. Then, we propose two linear program models, binary linear program and mixed integer program, to find the optimal deployment cost of time-aware business processes in cloud resources.
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Submitted on : Friday, October 16, 2020 - 4:10:49 PM
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  • HAL Id : tel-02969494, version 1

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Rania Ben Halima Kchaou. Cost optimization of business processes based on time constraints on cloud resources. Networking and Internet Architecture [cs.NI]. Institut Polytechnique de Paris, 2020. English. ⟨NNT : 2020IPPAS014⟩. ⟨tel-02969494⟩

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