Classifying Serialization Formats for Inter-Service Communication in Distributed Systems

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dc.citation.epage180
dc.citation.issue2
dc.citation.journalTitleДосягнення у кіберфізичних системах
dc.citation.spage175
dc.citation.volume9
dc.contributor.affiliationLviv Polytechnic National University
dc.contributor.affiliationSapienza University of Rome
dc.contributor.authorMaltsev, Eduard
dc.contributor.authorMuliarevych, Oleksandr
dc.contributor.authorRazzaque, Asmad
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2025-11-06T08:48:08Z
dc.date.created2024-02-27
dc.date.issued2024-02-27
dc.description.abstractThis study focuses on classifying serialization formats used in inter-service communication (ISC) within distributed systems and exploring their historical development. We have examined key features of human-readable formats such as XML, JSON, and YAML, binary formats like Protocol Buffers and Apache Avro, and columnar formats such as Apache Parquet and ORC, among others. Our results have indicated a significant shift toward binary formats optimized for speed and compactness in recent years. The industry demand score for Apache Avro and Google Protocol Buffers has been shown to be much higher than for Thrift. JSON remains on top, showing the best score for general technology adoption and industry demand score; Zero-copy formats like Can’n proto and Flatbuffers show lower industry demand scores in comparison to AVRO and Protocol Buffers but are useful in specific scenarios.
dc.format.extent175-180
dc.format.pages6
dc.identifier.citationMaltsev E. Classifying Serialization Formats for Inter-Service Communication in Distributed Systems / Eduard Maltsev, Oleksandr Muliarevych, Asmad Razzaque // Advances in Cyber-Physical Systems. — Lviv : Lviv Politechnic Publishing House, 2024. — Vol 9. — No 2. — P. 175–180.
dc.identifier.citationenMaltsev E. Classifying Serialization Formats for Inter-Service Communication in Distributed Systems / Eduard Maltsev, Oleksandr Muliarevych, Asmad Razzaque // Advances in Cyber-Physical Systems. — Lviv : Lviv Politechnic Publishing House, 2024. — Vol 9. — No 2. — P. 175–180.
dc.identifier.doidoi.org/10.23939/acps2024.02.175
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/117378
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofДосягнення у кіберфізичних системах, 2 (9), 2024
dc.relation.ispartofAdvances in Cyber-Physical Systems, 2 (9), 2024
dc.relation.references[1] Adibfar, A., Costin, A. (2021). Review of Data Serialization Challenges and Validation Methods for Improving Interoperability in Computing. In Civil Engineering, 522–529. DOI: 10.1061/9780784483893.065.
dc.relation.references[2] Friesel, D. and Spinczyk, O. (2021). Data Serialization Formats for the Internet of Things. Electronic Communications of the EASST, vol. 80. DOI: 10.14279/TUJ.ECEASST.80.1134.1078.
dc.relation.references[3] Luis, A., Casares, P., Cuadrado-Gallego, J., Patricio, M. (2021). PSON: A Serialization Format for IoT Sensor Networks. Sensors, vol. 21, no. 13, 4559. DOI: 10.3390/s21134559.
dc.relation.references[4] Maltsev, E., Muliarevych, O. (2024). Beyond JSON: Evaluating Serialization Formats for Space-Efficient Communication. Advances in Cyber-Physical Systems, vol. 9, no. 1, 9–15. DOI: 10.23939/acps2024.01.009.
dc.relation.references[5] Morschel, L. (2020). dCache – Efficient Message Encoding For Inter-Service Communication in dCache: Evaluation of Existing Serialization Protocols as a Replacement for Java Object Serialization. EPJ Web Conf., vol. 245, 05017. DOI: 10.1051/epjconf/202024505017.
dc.relation.references[6] Kumar, P., Agarwal, R., Shivaprasad, R., Sitaram, D., Kalambur, S. (2021). Performance Characterization of Communication Protocols in Microservice Applications. In 2021 International Conference on Smart Applications, Communications and Networking (SmartNets), Glasgow, 1–5. DOI: 10.1109/SmartNets50376.2021.9555425.
dc.relation.references[7] Mooney, P., Minghini, M. (2022). GEOSPATIAL DATA EXCHANGE USING BINARY DATA SERIALIZATION APPROACHES. Int. Arch. Photogram. Remote Sens. Spatial Inf. Sci., vol. XLVIII-4/W1-2022, 307–313. DOI: 10.5194/isprs-archives-XLVIII-4-W1-2022-307-2022.
dc.relation.references[8] Tiwary, G., Stroulia, E., Srivastava, A. (2021). Compression of XML and JSON API Responses. IEEE Access, vol. 9, 57426–57439. DOI: 10.1109/ACCESS.2021.3073041.
dc.relation.references[9] Weerasinghe, S., Perera, I. (2022). Evaluating the Inter-Service Communication on Microservice Architecture. In 2022 7th International Conference on Information Technology Research (ICITR), 1–6. DOI: 10.1109/ICITR57877.2022.9992918.
dc.relation.references[10] Parashar, A., Anand, P., Abraham, A. (2020). Performance Analysis and Optimization of Serialization Techniques for Deep Neural Networks. In Computer Vision, Pattern Recognition, Image Processing, and Graphics, 250–260. DOI: 10.1007/978-981-15-8697-2_23.
dc.relation.referencesen[1] Adibfar, A., Costin, A. (2021). Review of Data Serialization Challenges and Validation Methods for Improving Interoperability in Computing. In Civil Engineering, 522–529. DOI: 10.1061/9780784483893.065.
dc.relation.referencesen[2] Friesel, D. and Spinczyk, O. (2021). Data Serialization Formats for the Internet of Things. Electronic Communications of the EASST, vol. 80. DOI: 10.14279/TUJ.ECEASST.80.1134.1078.
dc.relation.referencesen[3] Luis, A., Casares, P., Cuadrado-Gallego, J., Patricio, M. (2021). PSON: A Serialization Format for IoT Sensor Networks. Sensors, vol. 21, no. 13, 4559. DOI: 10.3390/s21134559.
dc.relation.referencesen[4] Maltsev, E., Muliarevych, O. (2024). Beyond JSON: Evaluating Serialization Formats for Space-Efficient Communication. Advances in Cyber-Physical Systems, vol. 9, no. 1, 9–15. DOI: 10.23939/acps2024.01.009.
dc.relation.referencesen[5] Morschel, L. (2020). dCache – Efficient Message Encoding For Inter-Service Communication in dCache: Evaluation of Existing Serialization Protocols as a Replacement for Java Object Serialization. EPJ Web Conf., vol. 245, 05017. DOI: 10.1051/epjconf/202024505017.
dc.relation.referencesen[6] Kumar, P., Agarwal, R., Shivaprasad, R., Sitaram, D., Kalambur, S. (2021). Performance Characterization of Communication Protocols in Microservice Applications. In 2021 International Conference on Smart Applications, Communications and Networking (SmartNets), Glasgow, 1–5. DOI: 10.1109/SmartNets50376.2021.9555425.
dc.relation.referencesen[7] Mooney, P., Minghini, M. (2022). GEOSPATIAL DATA EXCHANGE USING BINARY DATA SERIALIZATION APPROACHES. Int. Arch. Photogram. Remote Sens. Spatial Inf. Sci., vol. XLVIII-4/W1-2022, 307–313. DOI: 10.5194/isprs-archives-XLVIII-4-W1-2022-307-2022.
dc.relation.referencesen[8] Tiwary, G., Stroulia, E., Srivastava, A. (2021). Compression of XML and JSON API Responses. IEEE Access, vol. 9, 57426–57439. DOI: 10.1109/ACCESS.2021.3073041.
dc.relation.referencesen[9] Weerasinghe, S., Perera, I. (2022). Evaluating the Inter-Service Communication on Microservice Architecture. In 2022 7th International Conference on Information Technology Research (ICITR), 1–6. DOI: 10.1109/ICITR57877.2022.9992918.
dc.relation.referencesen[10] Parashar, A., Anand, P., Abraham, A. (2020). Performance Analysis and Optimization of Serialization Techniques for Deep Neural Networks. In Computer Vision, Pattern Recognition, Image Processing, and Graphics, 250–260. DOI: 10.1007/978-981-15-8697-2_23.
dc.rights.holder© Національний університет “Львівська політехніка”, 2024
dc.rights.holder© Maltsev E., Muliarevych O., Razzaque A., 2024
dc.subjectBig Data applications
dc.subjectData communication
dc.subjectDistributed processing
dc.subjectEncoding
dc.subjectInformation exchange
dc.subjectProtocols
dc.subjectSoftware Architecture
dc.titleClassifying Serialization Formats for Inter-Service Communication in Distributed Systems
dc.typeArticle

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Advances In Cyber-Physical Systems. – 2024. – Vol. 9, No. 2