Fault tolerant computing in computational field model

M. Uehara
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引用次数: 6

Abstract

In large scale distributed systems, fault tolerant computing is important because each module may not be always reliable. Fault tolerant computing is not essentially needed to solve a problem. However, it is useful to execute a computing correctly. In this paper, we propose the usage of computational field model (CFM) as a framework to reuse such computing. Computational field is shared virtual space which abstracts distributed systems. It is possible to construct portable applications by applying algorithms to CFM. At first, we employ Triple Module Redundancy (TMR) as basic technique for fault tolerant computing in order to support real-time applications. Next, we assume the locality of fault occasion. For an example, physical crash causes faults locally. In such a case, each module should be distributed to increase system reliability. However, when they are distributed, system performance may be decreased because communication cost is increased. Thus, fault tolerance is related to system performance. In our approach, it is possible to accomplish both resource allocation and fault tolerant computing at the same time.
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计算场模型中的容错计算
在大规模分布式系统中,容错计算很重要,因为每个模块可能并不总是可靠的。容错计算并不是解决问题所必需的。然而,正确执行计算是有用的。在本文中,我们提出使用计算场模型(CFM)作为框架来重用这些计算。计算场是对分布式系统进行抽象的共享虚拟空间。通过将算法应用于CFM,可以构建可移植的应用程序。首先,为了支持实时应用,我们采用三模冗余(TMR)作为容错计算的基本技术。其次,我们假定故障场合的局部性。例如,物理崩溃导致本地故障。在这种情况下,为了提高系统的可靠性,应该将各个模块分散开来。但是,当它们分布时,由于通信成本的增加,可能会降低系统的性能。因此,容错与系统性能有关。在我们的方法中,可以同时完成资源分配和容错计算。
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