Deadline Constrained Energy-Efficient Scheduling for Workflows in Clouds

There is an increasing interest for cloud services to be provided in a more energy efficient way. The growing deployment of large-scale, complex workflow applications onto cloud computing hosts is being faced with crucial challenges in reducing the power consumption without violating the service level agreement (SLA). In this paper, we consider cloud hosts which can operate in different power states with different capacities respectively, and propose a novel scheduling heuristic for workflows to reduce energy consumption while still meeting deadline constraint. The proposed heuristic is evaluated using simulation with four different real-world applications. The observed results indicates that our heuristic does significantly outperform the existing approaches.