Data Compression Strategies for Enhancing IoRT Communications over Heterogeneous Terrestrial-Satellite Networks

P. 189–193.

Alexander Karnaukhov, Artem Idelevich, Alexey Rolich, Leonid Voskov

Data transmission over low-speed networks is a subject of global research interest, with a specific focus on overcoming limitations in satellite communication channels. However, little research has addressed the impact of compression on data transmission efficiency in heterogeneous networks using satellite links, especially in the context of the Internet of Remote Things and under poor terrestrial network infrastructure. This study explores various data compression algorithms customized for tiny data in such scenarios. It identifies effective algorithms when combined with ProtoBuf serialization, achieving compression ratios between 3.5 and 8.2 for JSON messages of 30 to 680 bytes using the Huffman algorithm with an extended dictionary. For messages sized 680 to 2,048 bytes, Protobuf combined with LZ78 achieves compression ratios of 3.5 to 4.5. Moreover, a novel data preprocessing method is introduced, boosting processing performance by up to 27 times for messages under 680 bytes in size. These findings contribute to IoRT data serialization and compression and can potentially enhance existing methods.

Keywords: data compression, Protobuf, Internet of Remote Things, terrestrial-satellite networks, Serialization, IORT, LEO Satellite, JSON

Publication based on the results of: Преодоление ограничений взаимодействия киберфизических систем в гетерогенных сетях удаленного интернета вещей с использованием методов машинного обучения (2023)

In book

2023 XVIII International Symposium Problems of Redundancy in Information and Control Systems (REDUNDANCY)

IEEE, 2023.