The successful functioning of telecommunication networks largely depends on the effectiveness of algorithms for detection and protection against overloads. The article describes the main differences that arise when forecasting, monitoring and managing congestion at the node level and at the channel level. An algorithm for detecting congestion by estimating the entropy of time distributions of traffic parameters is proposed. The entropy measures of data sets for various types of model distribution, in particular for the Pareto distribution, which optimally describes the behavior of self-similar random processes, were calculated and analyzed. The advantages of this approach include scalability, sensitivity to changes in distributions of traffic characteristics and ease of implementation and accessible interpretation.


telecommunication systems; self-similarity factor of network traffic; congestion detection

Airehrour D., Gutierrez J. A., Ray S. K.: SecTrust-RPL: A secure trust-aware RPL routing protocol for Internet of Things. Future Generation Computer Systems 93, 2019, 860–876 []. DOI:

Alashhab A. A., Zahid M. S. M., Azim M. A., Daha M. Y., Isyaku B., Ali S.: A Survey of Low Rate DDoS Detection Techniques Based on Machine Learning in Software-Defined Networks. Symmetry 14, 2022, 1563 []. DOI:

Bakhovskyy P. et al.: Stages of the Virtual Technical Functions Concept Networks Development. Cagáˇnová et al. (eds.): Advances in Industrial Internet of Things, Engineering and Management. EAI/Springer Innovations in Communication and Computing, 2021, 119–135 []. DOI:

Bedin A., Chiariotti F., Kucera S., Zanella A.: Optimal Latency-Oriented Coding and Scheduling in Parallel Queuing Systems. IEEE Transactions on Communications 70(10), 2022, 6471–6488 []. DOI:

Chughtai O., Badruddin N., Rehan M., Khan A.: Congestion Detection and Alleviation in Multihop Wireless Sensor Networks. Wireless Communications and Mobile Computing 2017, 9243019 []. DOI:

Desai R. M., Patil B. P., Sharma D. P.: Learning based route management in mobile ad hoc networks. Indonesian Journal of Electrical Engineering and Computer Science 7(3), 2017, 718–723 []. DOI:

Desmoulins N., Fouque P.A., Onete C., Sanders O.: Pattern Matching on Encrypted Streams. ASIACRYPT 2018. Lecture Notes in Computer Science 11272, Springer, Cham. []. DOI:

Divitskyi A., Salnyk S., Hol V., Sydorkin P., Storchak A.: Development of a model of a subsystem for forecasting changes in data transmission routes in special purpose mobile radio networks. Eastern-European Journal of Enterprise Technologies 3(9), 2021, 116–125 []. DOI:

Dobkach L.: Analysis of methods for recognizing computer attacks. Legal informatics 1, 2020, 67–75 [].

Durairaj M., Hirudhaya Mary Asha J.: The Internet of Things (IoT) Routing Security – A Study. International Conference on Communication, Computing and Electronics Systems. Lecture Notes in Electrical Engineering 637. Springer, Singapore 2020 []. DOI:

Hasan N., Mishra A, Ray A. K.: Fuzzy logic based cross-layer design to improve Quality of Service in Mobile ad-hoc networks for Next-gen Cyber Physical System. Engineering Science and Technology, an International Journal 35, 2022, 101099 []. DOI:

Hui W., Zijian C., Bo H.: A Network Intrusion Detection System Based on Convolutional Neural Network. Journal of Intelligent & Fuzzy Systems 38(6), 2020, 7623–7637 []. DOI:

Mangelkar S., Dhage S., Nimkar A.: A comparative study on RPL attacks and security solutions. International Conference on Intelligent Computing and Control (I2C2), 2017, 1–6 []. DOI:

Moroz S., Tkachuk A., Khvyshchun M., Prystupa S., Yevsiuk M.: Methods for Ensuring Data Security in Mobile Standards. Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska 12(1), 2022, 4–9 []. DOI:

Myneni S., Chowdhary A., Huang D., Alshamrani A.: A distributed deep defense against DDoS attacks with edge computing. Computer Networks 209, 2022, 108874 []. DOI:

Priyadarshini R., Rabindra K.: A deep learning based intelligent framework to mitigate DDoS attack in fog environment. Journal of King Saud University – Computer and Information Sciences 34(3), 2022, 825–831 []. DOI:

Rafe V., Mohammady S., Cuevas E.: Using Bayesian optimization algorithm for model-based integration testing. Soft Comput 26, 2022, 3503–3525 []. DOI:

Showail A., Tahir R., Zaffar M. F., Noor M. H., Al-Khatib M.: An internet of secure and private things: A service-oriented architecture. Computers & Security 120, 2022, 102776 []. DOI:

Tkachuk A. et al.: Basic Stations Work Optimization in Cellular Communication Network. Advances in Industrial Internet of Things, Engineering and Management, EAI. Springer Innovations in Communication and Computing, 2021, 1–19 []. DOI:

Toroshanko Y., Selepyna Y., Yakymchuk N., Cherevyk V.: Control of traffic streams with the multi-rate token bucket, in International Conference on Advanced Information and Communications Technologies AICT 2019, 2019, 352–355 []. DOI:

Verma A., Ranga V.: Addressing Flooding Attacks in IPv6-based Low Power and Lossy Networks. TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON), 2019, 552–557 []. DOI:

Yin C., Wang H., Yin X. et al.: Improved deep packet inspection in data stream detection. J Supercomput 75, 2019, 4295–4308 []. DOI:

Yungaicela-Naula N., Vargas-Rosales C., Pérez-Díaz J., Carrera D.: A flexible SDN-based framework for slow-rate DDoS attack mitigation by using deep reinforcement learning. Journal of Network and Computer Applications 205, 2022, 103444 []. DOI:

Zheng C., Li X., Liu Q., Sun Y., Fang B.: Hashing Incomplete and Unordered Network Streams. Advances in Digital Forensics XIV. DigitalForensics 2018. IFIP Advances in Information and Communication Technology 532. Springer, Cham. 2018 []. DOI:


Published : 2022-12-30

Yakymchuk, N., Selepyna, Y., Yevsiuk, M., Prystupa, S., & Moroz, S. (2022). MONITORING OF LINK-LEVEL CONGESTION IN TELECOMMUNICATION SYSTEMS USING INFORMATION CRITERIA. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 12(4), 26-30.

Natalia Yakymchuk
Lutsk National Technical University  Kazakhstan
Yosyp Selepyna 
Lutsk National Technical University  Ukraine
Mykola Yevsiuk 
Lutsk National Technical University  Ukraine
Stanislav Prystupa 
Lutsk National Technical University  Ukraine
Serhii Moroz 
Lutsk National Technical University  Ukraine