首页> 外文会议>International Workshop on Job Scheduling Strategies for Parallel Processing(JSSPP 2005); 20050619; Cambridge,MA(US) >Wave Scheduler: Scheduling for Faster Turnaround Time in Peer-Based Desktop Grid Systems
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Wave Scheduler: Scheduling for Faster Turnaround Time in Peer-Based Desktop Grid Systems

机译:Wave Scheduler:在基于对等方的桌面网格系统中安排更快的周转时间

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The recent success of Internet-based computing projects, coupled with rapid developments in peer-to-peer systems, has stimulated interest in the notion of harvesting idle cycles under a peer-to-peer model. The problem we address in this paper is the development of scheduling strategies to achieve faster turnaround time in an open peer-based desktop grid system. The challenges for this problem are two-fold: How does the scheduler quickly discover idle cycles in the absence of global information about host availability? And how can faster turnaround time be achieved within the opportunistic scheduling environment offered by volunteer hosts? We propose a novel peer-based scheduling method, Wave Scheduler, which allows peers to self organize into a timezone-aware overlay network using structured overlay network. The Wave Scheduler then exploits large blocks of idle night-time cycles by migrating jobs to hosts located in night-time zones around the globe, which are discovered by scalable resource discovery methods. Simulation results show that the slowdown factors of all migration schemes are consistently lower than the slowdown factors of the non-migration schemes. Compared to traditional migration strategies we tested, the Wave Scheduler performs best. However under heavy load conditions, there is contention for those night-time hosts. Therefore, we propose an adaptive migration strategy for Wave Scheduler to further improve performance.
机译:基于Internet的计算项目的最新成功,以及对等系统的快速发展,激发了人们对在对等模型下收集空闲周期的想法的兴趣。我们在本文中解决的问题是开发调度策略,以在基于对等方的开放式桌面网格系统中实现更快的周转时间。此问题的挑战有两个方面:在缺少有关主机可用性的全局信息的情况下,调度程序如何快速发现空闲周期?又如何在志愿者主持人提供的机会调度环境中实现更快的周转时间?我们提出了一种新颖的基于对等方的调度方法,即Wave Scheduler,它使对等方可以使用结构化覆盖网络将自身组织为一个时区感知的覆盖网络。然后,Wave Scheduler通过将作业迁移到位于全球夜间区域的主机来利用大量的空闲夜间周期,这些主机是通过可伸缩的资源发现方法发现的。仿真结果表明,所有迁移方案的减速因子始终低于非迁移方案的减速因子。与我们测试的传统迁移策略相比,Wave Scheduler的性能最佳。但是,在高负载条件下,那些夜间主机存在争用。因此,我们为Wave Scheduler提出了一种自适应迁移策略,以进一步提高性能。

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