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Scientific paper ID 2071 : 2021/2
![]() SELF-RECOVERING TELECOMMUNICATION NETWORK ELEMENT TOPOLOGICAL STRUCTURE OPTIMIZATION
BY COST CRITERION
Oleksandr Shefer1, Galina Cherneva2, Frhat Ali Alnaeri1 The main reason for overloading most telecommunication networks is the finite number of buffers in the switching nodes and the limited channel resource associated with the cost of the channels. Within the limits of the article the algorithm of optimization the self-recovering link of a telecommunication network is developed and possibility of reception technically realizable analytical decision of a problem is provided, using as the limiting condition of cost transfer quantity of the information falling for unit of channel capacity. The scientific novelty of solving this problem consists in using combined switching methods, in particular, in a packet network to transport long messages by hybrid channel switching. The identity of using cost functions of one or another kind, which simplifies the choice of the cost function that most fully corresponds to the conditions of a particular problem is described in the article.
телекоммуникационная сеть время задержки оптимизация плотности информационного потока самовосстановление пропускная способностьtelecommunication network delay time optimization information flow densities self-recovery channel capacityOleksandr Shefer Galina Cherneva Frhat Ali Alnaeri BIBLIOGRAPHY [1] Fang, Shuguang, Dong, Yuning and Shi, Haixian (2012), “Approximate Modeling of Wireless Channel Based on Service Process Burstiness”, Proceedings of the International Conference on Wireless Networks (ICWN), Athens: 1-7. Athens: The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing, (WorldComp). [2] Sobieraj M., Stasiak, M and Weissenberg, J. (2012), “Analytical model of the single threshold mechanism with hysteresis for multi-service networks”, IEICE Transactions on Communications, Vol. E95.B No. 1, pp. 120–132. [3] Kurose, J. and Ross, K. (2017), Computer networking: a top–down approach, 7th ed., Harlow: Pearson, 864 p. [4] Viacheslav Davydov and Daryna Hrebeniuk (2020), Development the resources load variation forecasting method within cloud computing systems, Advanced Information Systems, Vol. 4, No. 4, pp. 128–135, DOI: https://doi.org/10.20998/2522-9052.2020.4.1... [5] Shefer, О.V. and Alnaeri, Frhat Ali (2020), “Optimum flow distribution in the network with adaptive data transfer”, Electronics and Control Systems, No. 4(66), pp.45-50, DOI: https://doi.org/10.18372/1990-5548.66.15254 |