Towards adaptive scheduling of tasks in transactional workflows

The paper discusses dynamic workload management in transaction processing systems where the workload consists of multiple classes of units of work, including workflows comprised of interdependent tasks. Business requirements specify that differing levels of service must be provided to different classes of work, thus it is natural to specify performance goals per work class, that reflect the business requirements for the work class as well as the inherent resource demands of the units of work. Adaptive algorithms have been proposed for the satisfaction of performance goals of transaction classes. Scheduling the execution of complete workflows, which are multi-transaction units of work, is complicated by the need for task coordination, due to both control and data flow dependencies among tasks. Current transaction processing monitors provide infrastructure for the coordination of tasks by means of queueing facilities. We draw on previous work on goal-oriented resource management to design adaptive task scheduling algorithms. A detailed simulator of transaction processing systems with a queueing facility has been developed, with the specific aim to study the performance for workloads that include multi-transaction units of work