Structural properties and conditional diagnosability of star graphs by using the PMC model

研究成果: Article同行評審

67 引文 斯高帕斯(Scopus)

摘要

Processor fault diagnosis has played an important role in measuring the reliability of a multiprocessor system; the diagnosability of many well-known multiprocessor systems has been widely investigated. Conditional diagnosability is a novel measure of diagnosability. It includes a condition whereby any fault set cannot contain all the neighbors of any node in a system. In this paper, the conditional diagnosability of star graphs by using the PMC model is evaluated. Several new structural properties of star graphs are derived. Based on these properties, the conditional diagnosability of an n-dimensional star graph is determined to be 8n-21 for n≥ 5.

原文English
文章編號6671606
頁(從 - 到)3002-3011
頁數10
期刊IEEE Transactions on Parallel and Distributed Systems
25
發行號11
DOIs
出版狀態Published - 2014 11月 1

All Science Journal Classification (ASJC) codes

  • 訊號處理
  • 硬體和架構
  • 計算機理論與數學

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