The paper presents a novel efficient encoding and decoding method for self-correction and anti-interference used in big data product tracing system based on the cyclic code theory. The principle of constructing code set is first illustrated. Then the specific encoding and decoding methods suitable for the algebra rules are invented in sequence for efficiency. At last, to test the new coding system, the paper accelerates the decoding time by OpenMP more than 36 times. The error-correcting code presents its perfect recovery property with a recovery rate of more than 95% under 60% damage rate. In analyzing its efficiency, the encoding process only costs 0.0045 second in average while the time of decoding method will increase with the damage rate’s ascending, but it can be controlled within 16 seconds. In comparison to other coding patterns in the references, the newly error-correcting and anti-interference coding method achieves a balance in complexity, encoding rate, and decoding time with its priority in recovering rate under the damage rate of 60%.

中文翻译：

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一种跟踪商品大数据信息的纠错抗干扰编码方法

本文基于循环码理论，提出了一种用于大数据产品追溯系统的自纠抗干扰高效编解码方法。首先说明构建代码集的原理。然后依次发明适合代数规则的特定编码和解码方法以提高效率。最后，为了测试新的编码系统，论文通过OpenMP将解码时间加快了36倍以上。纠错码表现出完美的恢复特性，在60%的损坏率下恢复率超过95%。分析其效率，编码过程平均仅花费0.0045秒，而解码方法的时间随着损坏率的上升而增加，但可以控制在16秒内。