Orchestrating secure workflows for cloud and grid services

The modern design of business and scientific IT landscapes is based upon service-oriented architectures. In doing so, small functional units are encapsulated as services accessible via standardized interfaces. Grid and Cloud computing both employ such services: Grid computing provides access to mostly scientifically used compute resources and data. Cloud computing is a commercially-driven, recently emerging technology that offers services to access compute power, platforms, and software solutions. Nowadays, workflows are the preferred means for the combination of services into added value service chains representing functional business processes or complex scientific experiments. However, the advantages of integrating services from all three domains (business, science, and Cloud computing) into one workflow is not exploited sufficiently. The integration of external services within workflows raises various challenges. This thesis presents a novel architecture for a workflow engine that is capable of integrating services from all three domains. It starts with an analysis of workflow life cycles and infers requirements from these. Additionally, it considers the idea of providing a Cloud service for workflow orchestration. This service offers effective means to deploy and execute workflows completely on external resources. Simultaneously, it allows elasticity and fair billing models in the context of Cloud computing. The resulting architecture is based on standards without creating a new proprietary workflow description language dialect in order to increase acceptance and sustainability. It especially targets security and communication barriers, which originate from the diversity of service providers as well as handling stateful services with default WS-BPEL activities. The architecture is evaluated with respect to its requirements and in two exemplary reallife business scenarios. Furthermore, the thesis illustrates the general applicability, with some limitations, to scientific workflows with the help of example workflows for typical scientific tasks. Finally, it analyses the performance of the new components.

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