Dynamic prioritization of transactions using threshold-prices

Prioritization of business processes in distributed transaction processing systems is applied to circumvent drawbacks resulting from queueing effects. These effects arise because of increasing workload of business processes using shared services. To predict the performance of such systems, typically queueing and simulation models are used and prioritization schemes are created for specific business process definitions and demand mixes. Unfortunately, the derived solution may get obsolete after every demand-change and process re-engineering cycle. We propose an approach to adapt the prioritization by continuously aligning threshold-prices for the service usage reflecting the opportunity costs of using a service. The prioritization of a process is then reduced by the sum of current threshold prices of services invoked by that process. First we show that this approach is asymptotically optimal with an increasing number of business processes and workload requests. Second, we conduct simulations to show that the dynamic prioritization approach dominates common static prioritization approaches even in scenarios with moderate numbers of processes and process requests.