基于扩散的全分布式容错任务管理
Fully distributed and fault tolerant task management based on diffusions
摘要：
任务管理是计算网格的一个重要组成部分。其目的是根据全局调度策略和节点的本地资源的视图来分配任务。一个对等的任务管理方法涉及到网格的更好的可伸缩性和更高的容错。但是，必须提出一些机制来避免计算的复制任务，这可能会降低效率，增加节点的负载。同样，这些机制必须限制交换的消息的数量，以避免网络过载。在以前的论文中，我们已经提出了两种方法的任务管理称为主动和被动。这些方法基于随机游走：它们是完全分布式和容错的。每个节点拥有一个本地任务状态集，由于随机游走而更新，每个节点负责本地分配。在这里，我们提出了三种方法来提高主动方法的效率。这些新方法是基于一个流传的词。节点的本地任务状态集的更新由于周期性的扩散沿树从循环词。特别是，我们表明，这些方法提高了主动方法的效率：它们产生较少的重复任务。这三种方法也是完全分布式和容错的。另一方面，循环词可以用于其他应用，如资源管理或节点同步。
英文摘要：
The task management is a critical component for the computational grids. The aim is to assign tasks on nodes according to a global scheduling policy and a view of local resources of nodes. A peer-to-peer approach for the task management involves a better scalability for the grid and a higher fault tolerance. But some mechanisms have to be proposed to avoid the computation of replicated tasks that can reduce the efficiency and increase the load of nodes. In the same way, these mechanisms have to limit the number of exchanged messages to avoid the overload of the network. In a previous paper, we have proposed two methods for the task management called active and passive. These methods are based on a random walk: they are fully distributed and fault tolerant. Each node owns a local tasks states set updated thanks to a random walk and each node is in charge of the local assignment. Here, we propose three methods to improve the efficiency of the active method. These new methods are based on a circulating word. The nodes local tasks states sets are updated thanks to periodical diffusions along trees built from the circulating word. Particularly, we show that these methods increase the efficiency of the active method: they produce less replicated tasks. These three methods are also fully distributed and fault tolerant. On the other way, the circulating word can be exploited for other applications like the resources management or the nodes synchronization.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
