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Resource allocation and resource planning, especially in a SOA and grid environment, become crucial. Particularly, in an environment with a huge number of workflow consumers requesting a decentralized cross-organizational workflow, performance evaluation and execution-management of service-oriented workflows gain in importance. The need for an effective and efficient workflow management forces enterprises to use intelligent optimization models and heuristics to compose workflows out of several services under real-time conditions. This paper introduces the required architecture workflow performance extension - WPX.KOM for resource planning and workload prediction purposes. Furthermore, optimization approaches and a high-performance heuristic solving the addressed resource planning problem with low computational overhead are presented.