Compression Algorithm in Mobile Packet Core

Sammanfattning: Context: Data compression is the technique that is used for the fast transmission of the data and also to reduce the storage size of the transmitted data. Data compression is the massive and ubiquitous technology where almost every communication company make use of data compression. Data compression is categorized mainly into lossy and lossless data compression. Ericsson is the telecommunication company that deals with millions of user data and, all these data get compressed using the Deflate compression algorithm. Due to the compression ratio and compression speed, the deflate algorithm is not optimal for the present use case(compress twice and decompress once) of Ericsson. This research is all about finding the best alternate algorithm which suits the current use case so that the deflate algorithm can replace it. Objectives: The objective of the research is to replace the Deflate algorithm with the algorithm, which is useful for compressing the Serving GPRS Support Node-Mobility Management Entity(SGSN-MME) user data effectively. The main objectives to achieve this goal are: Investigating the better algorithm which fits the SGSN-MME compression patterns, investigating the few alternate algorithms for Deflate algorithm, the SGSN- MME dataset used to perform experimentation, the experiment should perform by using all selected algorithms on the dataset, the results of the experiment were compared based on the compression factors, based on the performance of algorithm the Deflate algorithm will get replaced with the suitable algorithm. Methods: In this research, a literature review performed to investigate the alternate algorithms for the Deflate algorithm. After selecting the algorithm, an experiment conducted on the data which was provided by Ericsson AB, Gothenburg and based on the compression factors like compression ratio, compression speed the performance of the algorithm evaluated. Results: By analyzing the results of the experiment, Z-standard is the better performance algorithm with the optimal compression sizes, compression ratio, and compression speed. Conclusions: This research concludes by identifying an alternate algorithm that can replace the Deflate algorithm and also which is suitable for the present Use case.