Efficient dynamic task scheduling in virtualized data centers with fuzzy prediction
Efficient dynamic task scheduling in virtualized data centers with fuzzy prediction
复制标题
具有模糊预测的虚拟化数据中心高效动态任务调度
DOI：
10.1016/j.jnca.2010.06.001
复制
发表时间：
2011-07-01
影响因子：
8.7
通讯作者：
Chu, Xiaowen
中科院分区：
文献类型：
--
作者：
Kong, Xiangzhen;Lin, Chuang;Chu, Xiaowen
系统虚拟化为虚拟化数据中心提供了低成本、灵活、强大的执行环境，在云计算的基础设施中扮演着重要的角色。然而，虚拟化也带来了一些挑战，特别是对资源管理和任务调度。提出了一种有效的虚拟化数据中心动态任务调度方案。综合考虑可用性和响应性能，建立了虚拟数据中心任务调度的一般模型，并将其表述为双目标优化问题。针对虚拟服务器节点的不确定工作负载和模糊可用性，利用I型和II型模糊逻辑系统，给出了一种优美的模糊预测方法。提出了一种在线动态任务调度算法SALAF，并对其性能进行了评价。实验结果表明，该算法可以提高虚拟化数据中心的总可用性，同时提供良好的响应性能。(C)2010爱思唯尔有限公司保留所有权利。
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. (C) 2010 Elsevier Ltd. All rights reserved.