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An optimal resource allocation is desired to increase the efficiency of systems processing business or scientific workflows. These systems include the processing of workflows in distributed computing environments such as grid or cloud computing. Current approaches used in this systems consider QoS-requirements as quality, speed or costs in the resource allocation process and just select the resources that satisfy these requirements. However, the selection of a resource should not be based solely on whether a resource meets the QoS-requirements or not, because it does not imply that a task is processed satisfactory by the selected resource according to its content. To evaluate resources regarding this aspect, trust models can be used. But current trust models are not specifically designed to model trust in distributed computing environments, hence handling the dynamics of business or scientific workflows that constantly change their requirements and conditions. In this paper, we present approaches which improve current trust models according to the problems mentioned. Thereby, the degree of automation in the trust evaluation process will be increased as well. Finally, in combination with an adjusted trust level workflow, the presented approach allows an optimal resource allocation for grid or cloud computing service providers.