Faulty Node Detection in Distributed Systems Using BCH Code

Prasetiadi, Agi; Kim, Dong-Seong

doi:10.1109/lcomm.2013.020413.122463

Cited by 11 publications

(6 citation statements)

References 10 publications

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“…A fault node detection scheme for distributed systems was proposed in [15] using BCH and CRC code. Code combination results in increased performance with respect to the detection of faulty nodes.…”

Section: Related Workmentioning

confidence: 99%

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Enhanced faulty node detection with interval weighting factor for distributed systems

2021

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This paper proposes an enhanced faulty node detection method using interval weighting factor, which monitors node behavior using pseudo-random Bose-Chaudhuri-Hocquenghem (BCH) code for distributed networked control systems. Master node collects the replacement of the cyclic redundancy check (CRC) codes by a single-bit BCH code of each slave node. However, BCH code can only obtain error position of the suspected faulty node without consideration of channel nodes. Hence, suspected error nodes are saved within the detected error interval and normalized using the weighting factor, which is carried out during sequential check, for interpretation. Fault judgement is carried out to adequately interpret the data, to guarantee detection accuracy of the detected error. The data is represented by statistical characteristic of the raw data and filtered data. This scheme can be applied to detect and prevent the severe damage by node failure. The simulation results prove the effectiveness of the interval faulty weighting factor, in obtaining raw data from the monitoring of the BCH code and filtered data, which are more accurate representation than the raw data. Moreover, the characteristics of the observed data were verified as the evaluation result of the suspected faulty node.

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Section: Related Workmentioning

confidence: 99%

“…This paper presents an extended version of the previous work [15] wherein the main problem and solution were discussed. The introduction of fault judgement with respect to the weighting factor of suspected faulty node is the main contribution of this paper.…”

Section: Introductionmentioning

confidence: 99%

Enhanced faulty node detection with interval weighting factor for distributed systems

2021

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“…The performance of the distributed system is affected by network-induced parameters such as delays, jitters, packet losses and link failures [1], [2]. This system has heavy application, such as those in the fields of aerospace, military visual processing, or industrial computer processors [3]. Due to large variation of data size, signal processing was needed to reconstruct the data.…”

Section: Introductionmentioning

confidence: 99%

Image Transmission in Military Network Using Bézier Curve

Rizal¹,

Kim²

2015

JACN

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Abstract-This paper proposed a method for reconstruct image by using Bézier Curve function. One of the causes of errors in image reconstruction is lack of sampling. In order to solve that problem, this paper proposes a method by using Bézier Curve to interpolate data between sampling points to reduce the error. The proposed method is compared to the previous works; compressive sampling and discrete Fourier transform (DFT). Compressive sampling is a method which has small number of data sample and DFT is used to perform Fourier analysis in many practical applications in digital signal processing. The result shows that image reconstruction using Bézier curve has closer quality to the original image compared to compressive sampling and DFT while it can maintain small size of reconstructed images.

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“…In industrial real-time network such as Fieldbus where the data is composed of control and I/O data, an error correction such BCH can be used to overcome the problems which are not only data integrity, but also its node integrity [7]. It presented the possibility to notify the faulty node in the industrial network.…”

Section: Introductionmentioning

confidence: 99%