Compression strategy of structured text based on prior dictionary for data distribution system

Kefei Li; Yijiang Jia; Yunhui Ji; Baodi Xie; Wei Zhang; Ping Lu; Jincai Chen

doi:10.1117/12.2659601

22 November 2022 Compression strategy of structured text based on prior dictionary for data distribution system

Kefei Li, Yijiang Jia, Yunhui Ji, Baodi Xie, Wei Zhang, Ping Lu, Jincai Chen

Proceedings Volume 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022); 1247519 (2022) https://doi.org/10.1117/12.2659601
Event: Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 2022, Hulun Buir, China

Abstract

Data distribution service (DDS) is a middleware API standard from Object Management Group (OMG), which transfers data using a publisher-subscriber model. The number of distributed nodes deployed in today's DDS communication system can reach tens of thousands, thus improving the efficiency of the communication system is important. In this work we present a structured text encoding strategy based on prior dictionary. This compression method has considerable compression effect on structured text such as HTML. In our evaluation, the average data compression rate is reduced by 7.07%, and the average system latency is reduced by 8.61% comparing to Zlib.

Citation Download Citation

Kefei Li, Yijiang Jia, Yunhui Ji, Baodi Xie, Wei Zhang, Ping Lu, and Jincai Chen "Compression strategy of structured text based on prior dictionary for data distribution system", Proc. SPIE 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 1247519 (22 November 2022); https://doi.org/10.1117/12.2659601

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