Autonomous Parameter Adjustment Method for Lossless Data Compression on Adaptive Stream-Based Entropy Coding
Autonomous Parameter Adjustment Method for Lossless Data Compression on Adaptive Stream-Based Entropy Coding
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DOI：
10.1109/access.2020.3029705
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发表时间：
2020
期刊：
影响因子：
3.9
通讯作者：
S. Yamagiwa;Suzukaze Kuwabara
中科院分区：
文献类型：
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作者：
S. Yamagiwa;Suzukaze Kuwabara
随着通信数据路径的速度在这十年中由于高数据速率而急剧提高，需要演进技术来解决快速通信实现。本文主要研究数据压缩技术来加快通信数据的传输速度，提出了一种基于流的数据压缩方法ASE编码。该算法基于瞬时数据熵对数据流进行压缩，压缩过程无需缓冲和停顿。它也适合于硬件实现。然而，基于流的数据压缩的工作原理与敏感的参数，影响数据压缩比。如果参数是静态配置的，它不遵循动态的数据熵，因此，数据压缩性能变得不稳定。在本文中，我们将传播的参数，讨论这些参数的行为，并提出其自主调整方法。我们还将提出调整算法，这些参数遵循的输入数据流的数据熵自主。通过对算法的实验评估，我们将确认参数的调整取决于数据流中的数据熵。然后，压缩比变得稳定，因为压缩器利用最小熵自适应。
As speed of communication data path is drastically improved in this decade due to the high data rate, evolutional technology is demanded to address the fast communication implementation. In this paper, we focus on data compression technology to speed up the communication data path. We have proposed a stream-based data compression called ASE coding. It compresses data stream based on the instantaneous data entropy without buffering and stalling for the compression processes. It is also suitable for hardware implementation. However, the stream-based data compression works heuristically with sensitive parameters that affect to the data compression ratio. If the parameters are statically configured, it does not follow the dynamic data entropy, and thus, the data compression performance becomes unstable. In this paper, we will disseminate the parameters, discuss the behaviors of those parameters and propose its autonomous adjustment methods. We will also propose adjustment algorithms for those parameters that follow the data entropy of the input data stream autonomously. Through experimental evaluations applying the algorithms, we will confirm the parameters are adjusted with depending on the data entropy in the data stream. And then, the compression ratio becomes stable as the compressor exploits the minimal entropy adaptively.