High fault-tolerant performance of the divide-and-swap cube network

IF 0.9 4区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS Theoretical Computer Science Pub Date : 2024-09-06 DOI:10.1016/j.tcs.2024.114834
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Abstract

Two crucial metrics used to evaluate the fault tolerance of interconnection networks are connectivity and diagnosability. By improving the connectivity and diagnosability of the interconnection network, its fault tolerance can be enhanced. In this paper, we focus on determining the g-extra connectivity (0g10) of the divide-and-swap cube DSCn, as well as its diagnosability based on the pessimistic diagnosis strategy and g-extra precise diagnosis strategy, under the PMC and MM* models. The research analysis suggests that compared with some other connectivity and diagnosability of DSCn, such as classical connectivity, structure connectivity, super connectivity, and classical diagnosability, the extra connectivity/diagnosability and pessimistic diagnosability of DSCn enable it to have a higher fault tolerance. Moreover, we propose two O(Nlog2N) effective diagnosis algorithms of DSCn: the g-extra diagnosis algorithm (EX-DiagnosisDSCn) and the pessimistic diagnosis algorithm (PE-DiagnosisDSCn), where the EX-DiagnosisDSCn algorithm can accurately diagnose the state of all processors in DSCn.

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分插立方体网络的高容错性能
用于评估互连网络容错性的两个关键指标是连通性和可诊断性。通过提高互连网络的连通性和可诊断性,可以增强其容错能力。本文重点研究在 PMC 和 MM* 模型下,基于悲观诊断策略和 g-extra 精确诊断策略,确定分插立方体 DSCn 的 g-extra 连接性(0≤g≤10)及其可诊断性。研究分析表明,与 DSCn 的其他连接性和可诊断性(如经典连接性、结构连接性、超级连接性和经典可诊断性)相比,DSCn 的额外连接性/可诊断性和悲观可诊断性使其具有更高的容错性。此外,我们还提出了两种 O(Nlog2N) 有效的 DSCn 诊断算法:g-额外诊断算法(EX-DiagnosisDSCn)和悲观诊断算法(PE-DiagnosisDSCn),其中 EX-DiagnosisDSCn 算法可以准确诊断 DSCn 中所有处理器的状态。
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来源期刊
Theoretical Computer Science
Theoretical Computer Science 工程技术-计算机:理论方法
CiteScore
2.60
自引率
18.20%
发文量
471
审稿时长
12.6 months
期刊介绍: Theoretical Computer Science is mathematical and abstract in spirit, but it derives its motivation from practical and everyday computation. Its aim is to understand the nature of computation and, as a consequence of this understanding, provide more efficient methodologies. All papers introducing or studying mathematical, logic and formal concepts and methods are welcome, provided that their motivation is clearly drawn from the field of computing.
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