Framework for the comparative analysis of networking software libraries and its application to C++ networking solutions

Yehor Hrushevyy; Kostiantyn Zhereb

Journal: Volume 30, No. 3, 2025

Pages: 10 – 23

DOI: https://doi.org/10.62660/bcstu/3.2025.10

1,064 Views

Framework for the comparative analysis of networking software libraries and its application to C++ networking solutions

Yehor Hrushevyy, Kostiantyn Zhereb

Received 07.04.2025

Revised 10.08.2025

Accepted 15.09.2025

Abstract

The objective evaluation of networking libraries remains a critical challenge in software engineering, as inconsistent methodologies and application-specific code often obscure meaningful performance and usability differences. The aim of this study was to conduct a comprehensive comparison of three C++ networking libraries (Boost.Asio, Boost.Beast, and Poco.Net) based on the proposed universal framework. The research methodology included the development of a universal comparative framework, experimental implementation of software prototypes, load testing to collect quantitative indicators, and a structured qualitative assessment based on a number of defined criteria. The framework encompassed both quantitative metrics (throughput, latency and resource consumption) and qualitative criteria (Application Programming Interface ergonomics, feature completeness, stability, cross platform compatibility and development complexity), with all libraries assessed under identical software conditions. Using each library, two C++ client-server prototypes were implemented: the RESTful service ResourceMonitor and the real time streaming application GameOfLifeStreaming. The project structure was unified to eliminate variability in application logic and to focus analysis exclusively on library behaviour. Boost.Asio demonstrated advantages in latency sensitive scenarios and scenarios requiring fine grained control. Boost.Beast offered effective HTTP support with minimal performance overhead but limited protocol coverage. Poco.Net achieved the lowest memory footprint and maintained stable performance at high loads while supporting the widest range of protocols, albeit at the expense of higher latency and lower raw throughput, and requiring more complex configuration. The practical contribution lies in the reusable framework for evaluating other networking libraries, the integration of created components into diverse development workflows, and the provided guidelines for choosing the most appropriate library

Keywords

application performance evaluation; load testing; client-server architecture; quantitative and qualitative metrics collection; testbed configuration; modular architecture; throughput and latency measurement

References

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Suggested citation

Hrushevyy, Ye., & Zhereb, K. (2025). Framework for the comparative analysis of networking software libraries and its application to C++ networking solutions. Bulletin of Cherkasy State Technological University, 30(3), 10-23. https://doi.org/10.62660/bcstu/3.2025.10

[1] Amirkhanov, B., Amirkhanova, G., Kunelbayev, M., Adilzhanova, S., & Tokhtassyn, M. (2025). Evaluating HTTP, MQTT over TCP and MQTT over WEBSOCKET for digital twin applications: A comparative analysis on latency, stability, and integration. International Journal of Innovative Research and Scientific Studies, 8(1), 679-694. doi: 10.53894/ijirss.v8i1.4414.

[2] Anzt, H., Chen, Y.-C., Cojean, T., Dongarra, J., Flegar, G., Nayak, P., Quintana-Ortí, E.S., Tsai, Y.M., & Wang, W. (2019). Towards continuous benchmarking: An automated performance evaluation framework for high performance software. In PASC 2019: Proceedings of the platform for advanced scientific computing conference (article number 9). New York: Association for Computing Machinery. doi: 10.1145/3324989.3325719 .

[3] Ardarve, J., Finne, R., Hrustic, A., & Svennungsson, J. (2019). Enforcing privacy requirements on oblivious network agents - a software solution of a type system generated from COPPA. (Bachelor’s thesis, Chalmers University Of Technology, Gothenburg, Sweden).

[4] Baddi, Y., Sebbar, A., Zkik, K., Maleh, Y., Bensalah, F., & Boulmalf, M. (2023). MSDN-IoT multicast group communication in IoT based on software defined networking. Journal of Reliable Intelligent Environments, 10, 93-104. doi: 10.1007/s40860-023-00203-x .

[5] Butynets, D. (2023). Performance assessment of the different approaches to implementing network servers using C++ language. (Bachelor’s thesis, Ukrainian Ctholic University, Lviv, Ukraine).

[6] Che, M., & Tuo, M. (2016). Server program analysis based on HTTP protocol. MATEC Web of Conferences, 63, article number 05023. doi: 10.1051/matecconf/20166305023.

[7] Dawood, K.A., Zaidan, A.A., Sharif, K.Y., Ghani, A.A., Zulzalil, H., & Zaidan, B.B. (2023). Novel multi-perspective usability evaluation framework for selection of open source software based on BWM and group VIKOR techniques. International Journal of Information Technology & Decision Making, 22(1), 187-277. doi: 10.1142/ s0219622021500139.

[8] De La Mora, F.L., & Nadi, S. (2018). An empirical study of metric-based comparisons of software libraries. In Proceedings of the 14th international conference on predictive models and data analytics in software engineering (pp. 22-31). New York: Association for Computing Machinery. doi: 10.1145/3273934.3273937 .

[9] Denisova, E., Tiribilli, E., Luschi, A., Francia, P., Manetti, L., Bocchi, L., & Iadanza, E. (2024). Enabling reliable usability assessment and comparative analysis of medical software: A comprehensive framework for multimodal biomedical imaging platforms. Health and Technology, 14, 671-682. doi: 10.1007/s12553-024-00859-2.

[10] El-Hajj, R., & Nadi, S. (2020). LibComp: An IntelliJ plugin for comparing Java libraries. In Proceedings of the 28th ACM joint meeting on European software engineering conference and symposium on the foundations of software engineering (pp. 1591-1595). New York: Association for Computing Machinery. doi: 10.1145/3368089.3417922 .

[11] Kadusic, E., Zivic, N., Hadzajlic, N., & Ruland, C. (2022). The transitional phase of Boost. Asio and POCO C++ networking libraries towards IPv6 and IoT networking security. In 2022 IEEE international conference on smart internet of things (SmartIoT) (pp. 80-85). Suzhou: IEEE. doi: 10.1109/smartiot55134.2022.00022.

[12] Kayum, S.N., Alsalim, H., Tonellot, T., & Momin, A. (2020). A fault tolerant implementation for a massively parallel seismic framework. In 2020 IEEE high performance extreme computing conference (HPEC) (pp. 1-8). Waltham: IEEE. doi: 10.1109/hpec43674.2020.9286143.

[13] Loja, A., & Maita, T. (2024). Comparative evaluation of performance efficiency in terms of temporal behavior and resource utilization, according to the ISO/IEC 25,010 model, in a web application developed with Angular, React.js, and Vue.js. In G.F. Olmedo Cifuentes, D.G. Arcos Avilés & H.V. Lara Padilla (Eds.), Emerging research in intelligent systems. CIT 2023. Lecture notes in networks and systems (pp. 293-308). Cham: Springer. doi: 10.1007/978-3-031-52255-0_21 .

[14] Lu, F., Fang, T., Zhang, Z., Li, S., Chen, J., An, H., & Han, W. (2019). Improving the performance of MongoDB with RDMA. In IEEE international conference on high performance computing and communications (HPCC) (pp. 1004-1010). Zhangjiajie: IEEE. doi: 10.1109/hpcc/smartcity/dss.2019.00144.

[15] Mitrović, D., Ivanović, M., Vidaković, M., & Budimac, Z. (2015). A scalable distributed architecture for Web-Based software agents. In M. Núñez, N. Nguyen, D. Camacho & B. Trawiński (Eds.), Computational collective intelligence. Lecture notes in computer science (pp. 67-76). Cham: Springer. doi: 10.1007/978-3-319-24069-5_7.

[16] Nechaieva, T., Teslenko, O., Trokhaniak, V., & Makarevych, S. (2025). Modeling energy balances of a community under increased energy independence and greenhouse gas reduction. Machinery & Energetics, 16(1), 104-116. doi: 10.31548/machinery/1.2025.104 .

[17] Pasichnyk, Y. (2022). Performance analysis of synchronous and asynchronous parallel network server implementations using the C++ language. (Bachelor’s thesis, Ukrainian Ctholic University, Lviv, Ukraine).

[18] Petty, M.D., Kim, J., Park, S., & Lee, S. (2015). A methodology for quantitative assessment of the features and capabilities of software frameworks for model composition. International Journal of Modeling, Simulation, and Scientific Computing, 7(1), article number 1541002. doi: 10.1142/s1793962315410020.

[19] Pflugfelder, C. (2022). Asynchronous programs on loT devices. (Bachelor’s thesis, Institute for Formal Methods of Computer Science, Stuttgart, Germany).

[20] Sai, P.C., Karthik, K., Prasad, K.B., Pranav, C.V.S., & Divya, K.V. (2024). Real-time task manager: A Python-based approach using Psutil and Tkinter. In 2024 8th international conference on computational system and information technology for sustainable solutions (CSITSS) (pp. 1-6). Bengaluru: IEEE. doi: 10.1109/csitss64042.2024.10816758 .

[21] Samoydiuk, А., & Ostapchuk, О. (2024). Optimizing high-load systems with asynchronous programming techniques. In Modeling, control and information technologies: Proceedings of VII international scientific and practical conference (pp. 130-131). Rivne: National University Of Water And Environmental Engineering. doi: 10.31713/mcit.2024.036.

[22] Turchyn, O. (2025). Introduction of neural network technologies to optimise control of suckerrod pump installation. Machinery & Energetics, 16(1), 32-42. doi: 10.31548/machinery/1.2025.32.