云中多媒体应用中基于混合DAG的最优任务调度研究

云计算的平台优势使得它在多媒体应用中得到广泛使用。由于多媒体服务的多样性和异构性,如何将多媒体任务有效地调度至虚拟机进行处理成为当前多媒体应用的研究重点。对此,研究了云中多媒体最优任务调度问题,首先引入有向无环图来模拟任务中的优先级及任务之间的依赖性,分别对串行、并行、混合结构任务调度模型进行任务调度研究,根据有限资源成本将关键路径中任务节点融合,提出一种实用的启发式近似最优调度方法。实验结果表明,所提调度方法能够以最短的执行时间在有限的资源成本下完成最优的任务分配。

Optimal Task-level Scheduling Based on Multimedia Applications in Cloud

As an emerging computing paradigm,cloud computing has been increasingly used in multimedia applications.Because of the diversity and heterogeneity of multimedia services,how to effectively schedule multimedia tasks to multiple virtual machines for processing has become one fundamental challenge for application providers.So we studied task-level scheduling problem for cloud based multimedia applications.Firstly,we introduced a directed acyclic graph to mo-del precedence constraints and dependency among tasks in the hybrid structure.Based on the model,we studied the optimal task scheduling problem for the sequential,the parallel,and the mixed structures.Moreover,we combined the task nodes in the critical path according to the cost of limited resources.Lastly,we proposed a heuristic method to perform the near optimal task scheduling in a practical way.Experimental results demonstrate that the proposed scheduling scheme can optimally assign tasks to virtual machines to minimize the execution time.