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广西大学计算机与电子信息学院,广西 南宁 530004
[ "梁家荣(1966-),男,广西玉林人,博士,广西大学教授,主要研究方向为网络的故障诊断、并行与网络计算。" ]
[ "陈秒江(1992-),男,广西北流人,广西大学硕士生,主要研究方向为网络的故障诊断、并行与网络计算。" ]
网络出版日期:2017-08,
纸质出版日期:2017-08-25
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梁家荣, 陈秒江. 基于比较模型的扩展立方体网络的(t,k)-诊断度研究[J]. 通信学报, 2017,38(8):9-18.
Jia-rong LIANG, Miao-jiang CHEN. Research on(t,k)-diagnosability for augmented cube network under the comparison model[J]. Journal on communications, 2017, 38(8): 9-18.
梁家荣, 陈秒江. 基于比较模型的扩展立方体网络的(t,k)-诊断度研究[J]. 通信学报, 2017,38(8):9-18. DOI: 10.11959/j.issn.1000-436x.2017159.
Jia-rong LIANG, Miao-jiang CHEN. Research on(t,k)-diagnosability for augmented cube network under the comparison model[J]. Journal on communications, 2017, 38(8): 9-18. DOI: 10.11959/j.issn.1000-436x.2017159.
针对扩展立方体网络故障诊断问题,提出一种基于比较模型的(t,k)-故障诊断方法。首先,通过图论的方法研究n维扩展立方体网络(AQ
n
)的重要性质,根
据这些性质设计了一个基于比较模型的算法来寻找该扩展立方体网络的最大非故障组件。然后,利用所得的最大非故障组件来确定该网络系统的(t,k)-故障诊断度。最后,提出并证明了n维扩展立方体网络是(t,2n-1)-可诊断的。结果表明,n维扩展立方体网络的(t,2n-1)-诊断度
<math xmlns="http://www.w3.org/1998/Math/MathML"> <mfrac> <mrow> <msup> <mn>2</mn> <mrow> <mi>n</mi><mo>−</mo><mn>1</mn></mrow> </msup> <mo stretchy="false">(</mo><mn>2</mn><mi>n</mi><mo>−</mo><mn>2</mn><mo stretchy="false">)</mo><mtext>lb(</mtext><mn>2</mn><mi>n</mi><mo>−</mo><mn>3</mn><mo stretchy="false">)</mo></mrow> <mrow> <msup> <mrow> <mo stretchy="false">(</mo><mn>2</mn><mi>n</mi><mo>−</mo><mn>3</mn><mo stretchy="false">)</mo></mrow> <mn>2</mn> </msup> </mrow> </mfrac> </math>
远大于其条件诊断度(6n-17)及传统故障诊断度(2n-1)。
Aiming at the prob1em of fau1t diagnosis in the augmented cube network,(t,k)-fau1t diagnosis method based on the comparison mode1 was proposed.The important properties of the n-dimensiona1 augmented cube network(AQn)by the method of graph theory were sketched.Then a1gorithm based on the comparison mode1 to 1ocate the 1argest fau1t component in the network was presented.Furthermore,the(t,k)-diagnosabi1ity of the augmented cube network was ca1cu1ated by using the 1argest fau1t component obtained.Fina11y,it is proved that the n-dimensiona1 augmented cube network(AQ
n
)is(t,2n-1)-diagnosab1e.The resu1t shows that the(t,2n-1)-diagnosabi1ity of AQ
n
is
<math xmlns="http://www.w3.org/1998/Math/MathML"> <mfrac> <mrow> <msup> <mn>2</mn> <mrow> <mi>n</mi><mo>−</mo><mn>1</mn></mrow> </msup> <mo stretchy="false">(</mo><mn>2</mn><mi>n</mi><mo>−</mo><mn>2</mn><mo stretchy="false">)</mo><mtext>lb(</mtext><mn>2</mn><mi>n</mi><mo>−</mo><mn>3</mn><mo stretchy="false">)</mo></mrow> <mrow> <msup> <mrow> <mo stretchy="false">(</mo><mn>2</mn><mi>n</mi><mo>−</mo><mn>3</mn><mo stretchy="false">)</mo></mrow> <mn>2</mn> </msup> </mrow> </mfrac> </math>
,which is much 1arger than 6n-17,the conditiona1 diagnosabi1ity of AQ
n
.And the 1atter is sti11 1arger than 2n-1,the ordinary diagnosabi1ity of AQ
n
.
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