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Faulty processor identification for a multiprocessor system under the Malek model using an improved binary bat algorithm

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Abstract

A multiprocessor system should be able to identify and eliminate faults in time to avoid the paralysis of a whole system. This paper proposes an improved binary bat algorithm to identify faulty processors in a multiprocessor system. Compared with most existing works based on metaheuristic algorithms, the proposed algorithm employs a random initial population and does not require transfer functions. The exclusive-OR operation in the velocity equation is used to measure the distance between two individuals in binary space. To improve population diversity and avoid local optima, the mutation operator is integrated into the position update equation. A new local search strategy is proposed to strengthen the ability of local search in binary space. Experimental results show that the proposed algorithm based on the Malek model can maintain approximately \(100\%\) diagnostic accuracy in a small random initial population with fewer iterations and less CPU running time.

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All data included in this study are available upon request by contact with the corresponding author.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant 61862003, Grant 61862004, and in part by the Ph.D. Scientific Research Foundation of Guangxi University of Finance and Economics under Grant BS2021016.

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  1. Weixia Gui and Fulai Pan have contributed equally to this work.

Authors and Affiliations

  1. College of Information and Statistics, Guangxi University of Finance and Economics, Nanning, 530003, Guangxi, China

    Weixia Gui

  2. Information Technology Institute, China Railway Nanning Bureau Group Co., Ltd., Nanning, 530029, Guangxi, China

    Fulai Pan

  3. School of Computer and Electronics Information, Guangxi University, Nanning, 530004, Guangxi, China

    Fulai Pan, Dandan Zhu & Feng Li

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  1. Weixia Gui
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  2. Fulai Pan
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  4. Feng Li
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Correspondence to Weixia Gui.

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Gui, W., Pan, F., Zhu, D. et al. Faulty processor identification for a multiprocessor system under the Malek model using an improved binary bat algorithm. J Supercomput 79, 3791–3820 (2023). https://doi.org/10.1007/s11227-022-04790-z

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