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A Comparison Diagnosis Algorithm for Conditional Fault Local Diagnosis of Multiprocessor Systems

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New Trends in Computer Technologies and Applications (ICS 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1723))

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Abstract

An efficient diagnosis is very important for a multiprocessor system. In this paper, we present a \((\alpha ,\beta )\)-trees combination \(S(u,X,\alpha ,\beta )\) and give some conclusions about the local diagnosis. Based on the \((\alpha ,\beta )\)-trees combination, we give a conditional fault local diagnosis algorithm to identify the fault or fault-free status of each processor correctly under the MM\(^*\) model when the number of faulty nodes does not exceed \(\alpha +2\beta -3\) and every node has at least one fault-free neighboring node. According to our results, a connected network with a \((\alpha ,\beta )\)-trees combination \(S(u,X,\alpha ,\beta )\) for a node u is conditionally locally \((\alpha +2\beta -3)\)-diagnosable at node u and the time complexity of our algorithm to diagnose u is \(O(\alpha ^2\beta +\alpha \beta ^2)\). As an application, we show that our algorithm can identify all the faulty nodes of n-dimensional star graph \(S_n\) if the faulty node number does not exceed \(3n-8\). Compared with existing algorithms, our algorithm allows more faulty node in a multiprocessor system.

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Acknowledgments

This work is supported by Shin Kong Wu Ho Su Memorial Hospital National Yang Ming Chiao Tung University Joint Research Program (No. 111-SKH-NYCU-03), the National Natural Science Foundation of China (No. 61902113, 62172291) and the Doctoral Research Foundation of Henan University of Chinese Medicine (No. BSJJ2022-14).

Author information

Authors and Affiliations

  1. School of Information Technology, Henan University of Chinese Medicine, Zhengzhou, China

    Yali Lv

  2. Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan

    Cheng-Kuan Lin

  3. Undergraduate Degree Program of Systems Engineering and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan

    Cheng-Kuan Lin

  4. Computer Science and Information Engineering, Chung Cheng Institute of Technology, NDU, Taoyuan City, Taiwan

    Cheng-Kuan Lin

  5. Department of Computer and Information Science, Fordham University, New York, USA

    D. Frank Hsu

  6. School of Computer Science and Technology, Soochow University, Suzhou, China

    Jianxi Fan

Authors
  1. Yali Lv
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  2. Cheng-Kuan Lin
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  3. D. Frank Hsu
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  4. Jianxi Fan
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Corresponding author

Correspondence to Cheng-Kuan Lin .

Editor information

Editors and Affiliations

  1. National Cheng Kung University, Tainan, Taiwan

    Sun-Yuan Hsieh

  2. National Taipei University of Business, Taoyuan, Taiwan

    Ling-Ju Hung

  3. CNRS and University of Bordeaux, Talence, France

    Ralf Klasing

  4. National Taitung University, Taitung, Taiwan

    Chia-Wei Lee

  5. National Taipei University of Business, Taoyuan, Taiwan

    Sheng-Lung Peng

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Lv, Y., Lin, CK., Hsu, D.F., Fan, J. (2022). A Comparison Diagnosis Algorithm for Conditional Fault Local Diagnosis of Multiprocessor Systems. In: Hsieh, SY., Hung, LJ., Klasing, R., Lee, CW., Peng, SL. (eds) New Trends in Computer Technologies and Applications. ICS 2022. Communications in Computer and Information Science, vol 1723. Springer, Singapore. https://doi.org/10.1007/978-981-19-9582-8_11

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  • DOI: https://doi.org/10.1007/978-981-19-9582-8_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-9581-1

  • Online ISBN: 978-981-19-9582-8

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