|Title:||Cloud-based elasticity for business processes and data storage||Language:||English||Authors:||Waibel, Philipp||Qualification level:||Doctoral||Advisor:||Schulte, Stefan||Issue Date:||2020||Number of Pages:||178||Qualification level:||Doctoral||Abstract:||
Over the last decade, the concept of cloud computing found widespread adoption as a way to provide software services to customers. Elasticity is often named as one of the major reasons for using cloud computing. This thesis focuses on the resource-efficient execution of business processes on elastic cloud-based resources and the redundant and cost-efficient storage of data on elastic cloud storages. Business Process Management Systems are often relying on heavyweight Virtual Machines as cloud-based execution environment for business processes or are not utilizing elastic cloud resources at all, leading to limited elasticity. In this thesis, we propose a novel approach by using lightweight containers as cloud-based execution environment, which decreases the required resource consumption and increases the elasticity compared to Virtual Machines. We develop an elastic Business Process Management System and a resource provisioning approach that optimizes the execution of concurrent business processes for resource efficiency while Service Level Agreements are considered. Due to the high elasticity, availability, durability, and low IT maintenance cost, cloud storage services have gained popularity in recent years. However, the decision which cloud storage service is the most suitable one is not trivial and relying on only one cloud storage service involves the risk of vendor lock-in. One solution to avoid this, is the redundant usage of different cloud storage services. In this thesis, we propose three different resource provisioning approaches for the cost-efficient data storage on multiple cloud storage services, by considering long-term storage services, customer-defined Service Level Agreements and monitored data access patterns.
|Keywords:||Cloud Computing; Elasticity; Elastic Processes; Elastic Process Execution; Business Processes; Cloud Storage; Optimization for cost efficiency||URI:||https://doi.org/10.34726/hss.2020.86637
|DOI:||10.34726/hss.2020.86637||Library ID:||AC16111279||Organisation:||E194 - Institut für Information Systems Engineering||Publication Type:||Thesis
|Appears in Collections:||Thesis|
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checked on Jun 19, 2021
checked on Jun 19, 2021
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