Elastic Resource Provisioning for Cloud Workflow Applications

Abstract

Many workflow applications are moved to clouds for elastic capacities. Elastic resource provisioning is one of the most important problems. Realistic factors are involved, including an interval-based charging model, data transfer time, VM loading time, software setup time, resource utilization, and the workflow deadline. A multirule-based heuristic is proposed for the problem under study which contains two components: a deadline division and task scheduling. Taking into account the gaps between tasks, the impact of different critical paths and the precedence constraints, the workflow deadline is properly divided into task deadlines based on the solution of a relaxed problem. The relaxed problem is modeled by integer programming and solved by CPLEX. All tasks are sorted in terms of the developed depth-based rule. For different realistic factors, three priority rules are developed to allocate tasks to appropriate available time slots, from which a weighted rule is constructed for task scheduling. The weights are calibrated by random instances. Experiments are conducted using a benchmark realistic workflow. Experimental results show that the proposal is effective and efficient for realistic workflows.