论文标题
多云系统中任务图的经济有效的可靠性知识调度程序
A Cost Effective Reliability Aware Scheduler for Task Graphs in Multi-Cloud System
论文作者
论文摘要
许多科学工作流可以由有向的无环形图（DAG）表示，每个节点代表一个任务，并且只有当两个任务之间存在两个任务之间的依赖关系，则两个任务之间的边缘将在两个任务之间存在。由于这些工作流的计算要求的增加，它们被部署在云计算系统上。在此类系统上安排工作流程以实现某些目标（例如，MakePan，成本或可靠性最大化等）仍然是一个积极的研究领域。在本文中，我们提出了一种调度算法，用于在异质的多云系统中分配任务图的节点。拟议的调度程序考虑了许多实际问题，例如定价机制，折现方案和任务执行的可靠性分析。这是一种基于列表的启发式方法，可以根据需要租用VM的预期时间来分配任务。我们已经分析了提出的方法以了解其时间要求。我们对实际工作流进行了大量实验：FFT，Ligo，表观基因组学和随机工作流程，并观察到，在成本，MakePan和可靠性方面，所提出的调度程序的表现优于最高的出艺术品近高达12％，11％和1.1％。
Many scientific workflows can be represented by a Directed Acyclic Graph (DAG) where each node represents a task, and there will be a directed edge between two tasks if and only if there is a dependency relationship between the two i.e. the second one can not be started unless the first one is finished. Due to the increasing computational requirements of these workflows, they are deployed on cloud computing systems. Scheduling of workflows on such systems to achieve certain goals(e.g. minimization of makespan, cost, or maximization of reliability, etc.) remains an active area of research. In this paper, we propose a scheduling algorithm for allocating the nodes of our task graph in a heterogeneous multi-cloud system. The proposed scheduler considers many practical concerns such as pricing mechanisms, discounting schemes, and reliability analysis for task execution. This is a list-based heuristic that allocates tasks based on the expected times for which VMs need to be rented for them. We have analyzed the proposed approach to understand its time requirement. We perform a large number of experiments with real-world workflows: FFT, Ligo, Epigenomics, and Random workflows and observe that the proposed scheduler outperforms the state-of-art approaches up to 12%, 11%, and 1.1% in terms of cost, makespan, and reliability, respectively.
