Comparative analysis of .NET-based solutions for iterative task execution in distributed fault-tolerant systems

Teymur Zeynally


This paper presents the results of a comparative analysis of .NET-based solutions for iterative task execution in distributed fault-tolerant systems. The study examines peer-to-peer distributed systems capable of iteratively performing scheduled tasks. Among the compared solutions are Quartz, Hangfire, and Recurrent Worker Service. The research investigates the dependency of measurable metrics such as iteration execution accuracy, minimum execution interval, and resource consumption on external destabilizing factors, including infrastructure (node failures) and network issues (bandwidth, delays, packet loss). The methodological basis of the study is experimental. The experiment is conducted on two servers, with one hosting the application nodes and the other hosting nodes of a synchronously replicated storage system. A series of tests are conducted on the application nodes where network and infrastructure destabilizing factors are controlled and simulated. During the experiment, hardware metrics are measured, and telemetry is collected from the applications. An analysis and calculation of statistical parameters are conducted based on the collected data, after which the results are presented in the form of tables and diagrams. The results of this work can be applied in the design and optimization of distributed systems requiring high levels of fault tolerance and efficiency.

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H. Mykhailyshyn, N. Pasyeka, V. Sheketa, M Pasyeka., O. Kondur, & M. Varvaruk, “Designing network computing systems for intensive processing of information flows of data,” In Lecture Notes on Data Engineering and Communications Technologies, vol. 48, 2021

G. Blinowski, A. Ojdowska, & A. Przybylek, “Monolithic vs. Microservice Architecture: A Performance and Scalability Evaluation,” IEEE Access, vol. 10, pp. 20357-20374, 2022,

T. Distler, C. Bahn, A. Bessani, F. Fischer, & F. Junqueira, “Extensible distributed coordination,” In Proceedings of the 10th European Conference on Computer Systems, EuroSys 2015, 2015.

T. Zeynally, & D. Demidov, “Fault tolerance of distributed worker processes in corporate information systems and technologies,” Communications in Computer and Information Science, vol. 1703, pp.32-41, 2022,

T. Zeynally, Demidov, & L. Dimitrov, “Prioritization of Distributed Worker Processes Based on Etcd Locks,”. Communications in Computer and Information Science, vol. 1703, pp. 93-103, 2022.

T. Zeynally, & D. Demidov, “Evaluation of the Efficiency of Fault Tolerance Algorithms for Distributed Peer-To-Peer Worker Processes Connected Through a Key-Value Store,” Communications in Computer and Information Science, vol. 1821, pp. 87-98, 2023. 1821.

A. Troelsen, & P. Japikse, “Introducing C# and .NET (Core) 5,” In Pro C# 9 with .NET 5, 2021.

I. C. Schuszter, & M. Cioca, “An implementation of a fault-tolerant database system using the actor model,” MATEC Web of Conferences, vol. 342, 2021.

A. Natanzon, & E. Bachmat, “Dynamic synchronous/asynchronous replication,” ACM Transactions on Storage, vol. 9, no. 3, pp. 1-19, 2013.

Bryk, P., Malawski, M., Juve, G., & Deelman, E. (2016). Storage-aware Algorithms for Scheduling of Workflow Ensembles in Clouds. Journal of Grid Computing, 14(2).

R. Garg, M. Mittal, & L. H. Son, “Reliability and energy efficient workflow scheduling in cloud environment,” Cluster Computing, vol. 22, no. 4, pp. 1283-1297, 2019.

R. Sharma, N. Nitin, M. A. R., AlShehri & D. Dahiya, “Priority-based joint EDF–RM scheduling algorithm for individual real-time task on distributed systems,” The Journal of Supercomputing, vol. 77, pp. 890-908, 2021.

C. Li, J. Tang, T. Ma, X. Yang, & Y. Luo, “Load balance based workflow job scheduling algorithm in distributed cloud,” Journal of Network and Computer Applications, vol. 152, p. 102518, 2020.

HangfireIO/Hangfire.: website. – URL: (2024, April 12)

quartznet/quartznet.: website. – URL: (2024, April 12)

TeymurZeynally/RecurrentWorkerService: website. – URL: : (2024, April 12)

Docker overview: website. – URL: (2024, April 12)

Telegraf Docker Input Plugin: website. – URL: (2024, April 12)

Docker Traffic Control: website. – URL: (2024, April 12)

InfluxDB key concepts: website. – URL: (2024, April 12)

DateTimeOffset Ticks: website. – URL: (2024, April 12)


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