Efficient dynamic task scheduling in virtualized data centers with fuzzy prediction

System virtualization provides low-cost, flexible and powerful executing environment for virtualized data centers, which plays an important role in the infrastructure of Cloud computing. However, the virtualization also brings some challenges, particularly to the resource management and task scheduling. This paper proposes an efficient dynamic task scheduling scheme for virtualized data centers. Considering the availability and responsiveness performance, the general model of the task scheduling for virtual data centers is built and formulated as a two-objective optimization. A graceful fuzzy prediction method is given to model the uncertain workload and the vague availability of virtualized server nodes, by using the type-I and type-II fuzzy logic systems. An on-line dynamic task scheduling algorithm named SALAF is proposed and evaluated. Experimental results show that our algorithm can improve the total availability of the virtualized data center while providing good responsiveness performance.