A Similar Resource Auto-Discovery Based Adaptive Fault-tolerance Method for Embedded Distributed System

Kailong Zhang, Ke Liang, Xingshe Zhou, Kaibo Wang, Xiao Wu, Zhiyi Yang
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Abstract

Because of the resource constraints and high reliability requirement of Embedded Distributed System (EDS), some new fault-tolerance means, which are different from the traditional hardware- redundancy ones, should be studied. In this article, a fault-tolerance method that based on similar resources and related technologies are proposed and discussed. First, several mathematical models of key elements, such as computing nodes, similar nodes and tasks, are constructed. Then, the similarity computation methods and evaluation criteria are evinced by two different views: tasks and resources. Supported by theories above, numerous methods, such as similar nodes auto- discovery (SNAD) and its optimization one (oSNAD), redundant tasks auto-deployment, and reconfiguration policies of fault tasks and nodes are highlighted respectively. Simulation results show that these approaches and schemes can improve the adaptive fault-tolerance abilities of complicated embedded distributed systems.
基于相似资源自动发现的嵌入式分布式系统自适应容错方法
由于嵌入式分布式系统的资源约束和对可靠性的高要求,必须研究不同于传统的硬件冗余容错方法的新型容错方法。本文提出并讨论了一种基于相似资源和相关技术的容错方法。首先,构建了计算节点、相似节点和任务等关键要素的数学模型;然后,从任务和资源两个不同的角度论证了相似度计算方法和评价标准。在上述理论的支持下,重点介绍了类似节点自动发现(SNAD)及其优化方法(oSNAD)、冗余任务自动部署、故障任务和节点的重新配置策略等方法。仿真结果表明,这些方法和方案能够提高复杂嵌入式分布式系统的自适应容错能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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