关键词: 异构云, 电压调节, 能耗感知调度, 超启发式算法, 在线学习

Abstract: The research of energy-aware scheduling is essential to the sustainable development of cloud computing data center. The energy-aware scheduling is NP-Hard multi-objective problem. Most of task scheduling algorithms currently less take the energy consumption into account, and can’t manage the energy consumption flexibly. Stochastic search is a feasible method, however, this method has high computation overhead and the convergence speed is slow usually. In this paper, the energy-aware scheduling problem is treated as a constraint problem on heterogeneous cloud computing systems, i.e. performance constrained energy optimization, to manage the energy consumption flexibly. Besides, Dynamic Voltage Scaling （DVS） technique is used to build a simple efficient low-level heuristics set, and?on?this?basis it develops a Hyper-Heuristic scheduling algorithm based on On-line Learning （OLHH） to improve the convergence. The simulation experimental results show that the proposed method can manage the energy consumption flexibly and has an outstanding convergence performance than tradition stochastic search techniques.

Key words: heterogeneous cloud, dynamic voltage scaling, energy-aware scheduling, hyper-heuristics, online learning