A Deadline Constrained Critical Path Heuristic for Cost-Effectively Scheduling Workflows

Abstract

Effective use of elastic heterogeneous cloud resources represents a unique multi-objective scheduling challenge with respect to cost and time constraints. In this paper we introduce a novel deadline constrained scheduling algorithm, Deadline Constrained Critical Path (DCCP), that manages the scheduling of workloads on dynamically provisioned cloud resources. The DCCP algorithm consists of two stages: (i) task prioritization, and (ii) task assignment, and builds upon the concept of Constrained Critical Paths to execute a set of tasks on the same instance in order to fulfil our goal of reducing data movement between instances. We evaluated the normalized cost and success rate of DCCP and compared these results with IC-PCP. Overall, DCCP schedules with lower cost and exhibits a higher success rate in meeting deadline constraints.