Diagnosability of component-Composition graphs in the mm* model

Chia Wei Lee, Sun-Yuan Hsieh

研究成果: Article同行評審

4 引文 斯高帕斯(Scopus)

摘要

Diagnosability is an important metric for measuring the reliability of multiprocessor systems. This article adopts the MM* model and outlines the common properties of a wide class of interconnection networks, called component-composition graphs (CCGs), to determine their diagnosability by using their obtained properties. By applying the results to multiprocessor systems, the diagnosability of hypercube-like networks (including hypercubes, crossed cubes, Möbius cubes, twisted cubes, locally twisted cubes, generalized twisted cubes,and recursive circulants), star graphs, pancake graphs, bubble-sort graphs, and burnt pancake graphs, all of which belong to the class of CCGs, can also be computed.

原文English
文章編號27
期刊ACM Transactions on Design Automation of Electronic Systems
19
發行號3
DOIs
出版狀態Published - 2014 1月 1

All Science Journal Classification (ASJC) codes

  • 電腦科學應用
  • 電腦繪圖與電腦輔助設計
  • 電氣與電子工程

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