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Abstract

This article proposes an analytical model of a system with priorities servicing a mixture of different elastic traffic streams. The model presented in the article was developed as the extension of earlier works published by the authors. It utilizes the concept of equivalent bandwidth and then, following bandwidth discretization, uses the dependencies introduced on the basis of the assumptions adopted for the generalized Kaufman-Roberts formula and for the model of a full-availability group with traffic compression. The article presents a possibility of using the proposed model to model the radio interface in a multi-service mobile network and provides an example of the above with the interface of an LTE network. Since the proposed model is an approximate one, the results of the calculations are compared with the results of simulations. A comparison of the results confirms an acceptable level of accuracy of the model. The model can be successfully used in the analysis and design of links and nodes of telecommunication and computer networks.

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Authors and Affiliations

B. Nowak
ORCID: ORCID
M. Piechowiak
M. Stasiak
P. Zwierzykowski
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Abstract

Metallurgy is one of the key industries both in Russia and in the world. It has a significant influence on the situation in related industries. Therefore, the current state analysis of ferrous metallurgy production and its formation based on the short-term technological forecast is essential. Based on the foregoing, the research was aimed at analyzing the current state of ferrous metallurgy production in Russia and the impact of the COVID-19 pandemic on the prospects for industry development in the short term. The research studies the state of the ferrous metallurgy production in Russia and abroad before the COVID-19 pandemic, as well as the volume of industrial production in ferrous metallurgy and the industry structure. The COVID-19 pandemic has triggered a serious global recession, necessitating an analysis of the forecast for the development of the ferrous metallurgy industry. The research concludes that the Russian ferrous metals market is so far affected to a lesser extent compared to the European one.
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Bibliography

[1] Ryabov, I.V. (2013). Institutional factors of economic development in the steel industry in the Russian Federation. Ekonomika: vchera, segodnya, zavtra. 7-8, 59-71.
[2] Shatokha, V. (2016). Post-Soviet issues and sustainability of iron and steel industry in Eastern Europe. Mineral Processing and Extractive Metallurgy. 126, 1-8.
[3] MIT Emerging Trends Report (2013). Cambridge, MA: Massachusetts Institute of Technology. Retrieved from http://2013.forinnovations.org/upload/MIT_Technology_Review.pdf.
[4] Cuhls, K. (2003). From forecasting to foresight processes. new participative foresight activities in Germany. Journal of Forecasting. 22, 93-111.
[5] Harrington, E.C.Jr. (1965). The desirability function. Industrial quality control. 21(1), 494-498.
[6] Profile. 2017/2018. World steel association. Retrieved from https://www.worldsteel.org/en/dam/jcr:cea55824-c208-4d41-b387-6c233e95efe5/worldsteel+Profile+2017.pdf.
[7] World Steel Association (2018). Monthly crude steel and iron production statistics. Retrieved from https://www.worldsteel.org/publications/bookshop/productdetails.~2018-Monthly-crude-steel-and-iron-productionstatistics~PRODUCT~statistics2018~.html.
[8] Metalinfo.ru (2018). China continues to cut off excessive capacity. Retrieved from http://www.metalinfo.ru/ru/news/100765.
[9] World Steel Association (2017). Steel Statistical Yearbook 2017. Retrieved from https://www.worldsteel.org/en/dam/jcr:3e275c73-6f11-4e7f-a5d8-23d9bc5c508f/Steel% 2520Statistical%2520Yearbook%25202017_updated%2520version090518.pdf.
[10] World Steel Association (2017). 50 years of the World Steel Association. World Steel Association. Retrieved from https://www.worldsteel.org/en/dam/jcr:80fe4bd6-4eff-4690-96e6-534500d35384/50%2520years%2520of%2520worldsteel_EN.pdf.
[11] Dudin, M.N., Bezbakh, V.V., Galkina, M.V., Rusakova, E.P., Zinkovsky, S.B. (2019). Stimulating Innovation Activity in Enterprises within the Metallurgical Sector: the Russian and International Experience. TEM Journal. 8(4), 1366-1370.
[12] Kharlamov, A.S. (2012). Competitiveness issues of metallurgy. Position of Russia. Monograph. Moscow: Nauchnaya Kniga.
[13] Golubev, S.S, Chebotarev, S.S., Sekerin, V.D. & Gorokhova, A.E. (2017). Development of Employee Incentive Programmes regarding Risks Taken and Individual performance. International Journal of Economic Research. 14(7), 37-46.
[14] Deloitte (2020). Overview of the ferrous metallurgy market. Retrieved from https://www2.deloitte.com/ru/ru/pages/research-center/articles/overview-of-steel-and-ironmarket-2020.html.
[15] Katunin, V.V., Zinovieva, N.G., Ivanova, I.M., Petrakova, T.M. (2021). The main performance indicators of the ferrous metallurgy of Russia in 2020. Ferrous metallurgy. Bulletin of Scientific. Technical and Economic Information. 77(4), 367- 392. DOI: https://doi.org/10.32339/0135-5910-2021-4-367-392.
[16] National Credit Ratings (NCR) (2021). The metamorphoses of the pandemic. The forecast of recovery of the Russian economy branches as of June 2, 2021. Analytical Research. June 2, 2021. Retrieved from https://www.ratings.ru/files/research//corps/NCR_Recovery_Jun2021.pdf 24.
[17] Mingazov, S. (2021). Russian metallurgists have doubled payments to the budget. Forbes. Retrieved from https://www.forbes.ru/newsroom/biznes/430855-rossiyskiemetallurgi-udvoili-vyplaty-v-byudzhet.
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Authors and Affiliations

S.S. Golubev
1
V.D. Sekerin
1
A.E. Gorokhova
1
D.A. Shevchenko
1
A.Z. Gusov
2

  1. Moscow Polytechnic University, Bolshaya Semenovskaya Street, 38, Moscow, 107023, Russian Federation
  2. Peoples Friendship University of Russia (RUDN University), Miklukho-Maklaya Street, 6, Moscow, 117198, Russian Federation
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Abstract

In this paper, we propose a novel priority-aware solution named bypass to handle high- and low-priority traffic in multi-layer networks. Our approach assumes diversification of elastic optical spectrum to ensure additional resources reserved for emergency situations. When congestion occurs, the solution dynamically provides new paths, allocating a hidden spectrum to offload traffic from the congested links in the IP layer. Resources for a bypass are selected based on traffic priority. High-priority traffic always gets the shortest bypasses in terms of physical distance, which minimizes delay. Bypasses for low-priority traffic can be established if the utilization of the spectrum along the path is below the assumed threshold. The software-defined networking controller ensures the global view of the network and cooperation between IP and elastic optical layers. Simulation results show that the solution successfully reduces the amount of rejected high-priority traffic when compared to regular bypasses and when no bypasses are used. Also, overall bandwidth blocking probability is lower when our priority-aware bypasses are used.
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Authors and Affiliations

Edyta Biernacka
1
ORCID: ORCID
Piotr Boryło
1
ORCID: ORCID
Piotr Jurkiewicz
1
ORCID: ORCID
Robert Wójcik
1
ORCID: ORCID
Jerzy Domżał
1
ORCID: ORCID

  1. Institute of Telecommunications, AGH University of Science and Technology, Kraków, Poland
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Abstract

The purpose of the study is to analyze the current state of the cast iron production and to predict production volume and cost in the near future based on the analysis results. Cast iron is one of the most common materials used in various industrial sectors. Cast iron scrap processing is the least expensive and saves both money and time. It is produced both in Russia and abroad and is one of the export types. Cast iron production significantly influences other industrial sectors. All this confirms the relevance of the study. The novelty of the study consists in the identification of the leaders among the cast-iron producers in the world and Russian metallurgical companies, as well as the determination of trends in its production at the present stage of economic development. The increasing consolidation level of cast iron producers has been revealed: China, India, Japan, and Russia represented 85% of the cast iron global production in 2019. In Russia, nine metallurgical companies account for 80% of cast iron production. In general, cast iron production in the world is stable and the import share of cast iron is about 4%. Cast iron prices tend to decline. The work identifies the lower and upper limits of the possible range of the cast iron prices. The authors conclude that the declining prices of cast iron in Russia may make its production unprofitable.
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Bibliography

[1] Arab, N. (2017). Competitive nucleation in grey cast irons. Archives of Foundry Engineering. 17(4), 185-189.
[2] Metalbulletin.ru (2020). Cast iron: the first candidate for decline? Retrieved from: https://www.metalbulletin.ru/a/101.
[3] Hannapel, J. & Schmeisse, C. (2020). New EPA air emissions standards for iron and steel foundries. Modern Casting. 11, 42-45.
[4] Lipshaw, J. (2020). Environmental impact across their life cycles. Modern Casting, 10, 34-38.
[5] Promzn.ru (2020). Features of steel production: methods, technologies and raw materials. Retrieved from: https://promzn.ru/metallurgiya/proizvodstvo-stali.html.
[6] Stroiset.ru (2020). Analysis and trends in the development of the cast iron market. Retrieved from: https://www.stroiset.ru/analiz-i-tendencii-razvitiya-rynka-chuguna.
[7] Metallurgicheskii byulleten (2020). Chugunnye reki i rucheiki. [Cast iron rivers and rivulets. Metallurgical bulletin]. Retrieved from: https://www.metaltorg.ru/analytics /black/?id=759/.
[8] MIT Emerging Trends Report (2013). Cambridge, MA: Massachusetts Institute of Technology. Retrieved from: http://2013.forinnovations.org/upload/MIT_Technology_Review.pdf.
[9] World Steel Association. 50 years of the World Steel Association. Retrieved from: https://www.worldsteel.org/ publications/bookshop/product-details.~50-years-of-the-World-Steel-Association~PRODUCT~50-years-of-the-World-Steel-Association~.html.
[10] Metallosnabzhenie i sbyt: internet-zhurnal. (2018). Kitai prodolzhit sokrashchenie izbytochnykh moshchnostei. [China will continue to reduce excess capacity. Metal supply and sales]. Retrieved from: http://www.metalinfo.ru/ru/ news/100765.
[11] Shatokha, V. (2016). Post-Soviet issues and sustainability of ferrous metallurgy in Eastern Europe. Mineral Processing and Extractive Metallurgy, 3, 1-8.
[12] Businesstat (2017). Analiz mirovogo rynka chuguna v 2012-2016 gg, prognoz na 2017-2021 gg [Analysis of the global cast iron market between 2012 and 2016; the outlook for the period from 2017 to 2021]. Retrieved from: https://marketing.rbc.ru/research/39673//
[13] Profile 2018/2019. World Steel Association [electronic resource] Retrieved from: https://www.worldsteel.org/ publications/bookshop/product-details.~Profile-2017-2018~PRODUCT~Profile2017~.html.
[14] Steel Statistical Yearbook 2019. World Steel Association [electronic resource] Retrieved from: http:// https://www.worldsteel.org/publications/bookshop/product-details.~Steel-Statistical-Yearbook-2017~PRODUCT~SSY2017~.html.
[15] ACG (2020). Rynok chuguna v Rossii. Tekushchaya situatsiya i prognoz 2020-2024 gg. [Cast iron market in Russia. The current situation and the outlook for the period from 2020 to 2024]. Retrieved from: https://alto-group.ru/otchot/rossija/380-rynok-chuguna-tekushhaya-situaciya-i-prognoz-2014-2018-gg.html/.

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Authors and Affiliations

S.S. Golubev
1
V.D. Sekerin
1
A.E. Gorokhova
1
G.V. Komlatskiy
2
Y.I. Arutyunyan
2

  1. Moscow Polytechnic University, Bolshaya Semenovskaya Street, 38, Moscow, 107023, Russia
  2. Kuban State Agrarian University, Kalinina Street, 13, Krasnodar, 350044, Russia
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Abstract

In cellular networks, cells are grouped more densely around highly populated areas to provide more capacity. Antennas are pointed in accordance with local terrain and clutter to reduce signal shadows and interference. Hardware parameters are easily set during installation but difficult to change thereafter. In a dynamic environment of population migration, there is need to continuously tune network parameters to adapt the network performance. Modern mobile equipment logs network usage patterns and statistics over time. This information can be used to tune soft parameters of the network. These parameters may include frequency channel assignment or reuse, and transmitter radiation power assignment to provide more capacity on demand. The paper proposes that by combining the frequency and power assignments, further optimisation in resource allocation can be achieved over a traditional frequency assignment. The solution considers the interference, traffic intensity and use of priority flags to bias some edges. An Edge Weight Power and Frequency Assignment Algorithm is presented to solve the resource allocation problem in cellular networks. The paper also analyses the performance improvements obtained over that of the Edge Weight Frequency Assignment Algorithm. The results show that the proposed algorithm improves the performance of the Edge Weight Frequency Assignment Algorithm depending on the initial structure of the graph.

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Authors and Affiliations

O.S. Pharatlhatlhe
J.S.J. Daka
E. Gower
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Abstract

In the skeptical tradition self-consciousness was transparent and it served as a basis for expressing doubts and developing arguments leading to certainty. After the linguistic and naturalistic turns, contemporary philosophy developed skeptical arguments against certainty and epistemic priority of the data of self-consciousness (both reflective and pre-reflective). Self-reflection reports on the stream of consciousness ex post, but the reports are meager and dependent on subject’s conceptual scheme, while the pre- -reflective data is unclear. Two contemporary skeptical hypotheses have been developed: H. Putnam’s content externalism hypothesis and so-called Kripkenstein’s quus hypothesis. I put forth the question what kind of self is immune to erroneous misidentification. The immunity seems to be limited to the contentless self, reducible to the pre-discursive feeling of one’s own existence. There is no guarantee that any content whatsoever can be attributed to self without error. I cannot negate that I exist any more than I can negate that something external exists, but any description of either is fallible. So the content of self-consciousness is not in an epistemically better position than the content of external perception.

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Authors and Affiliations

Renata Ziemińska
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Abstract

The power distribution internet of things (PD-IoT) has the complex network architecture, various emerging services, and the enormous number of terminal devices, which poses rigid requirements on substrate network infrastructure. However, the traditional PD-IoT has the characteristics of single network function, management and maintenance difficulties, and poor service flexibility, which makes it hard to meet the differentiated quality of service (QoS) requirements of different services. In this paper, we propose the software-defined networking (SDN)- enabled PD-IoT framework to improve network compatibility and flexibility, and investigate the virtual network function (VNF) embedding problem of service orchestration in PD-IoT. To solve the preference conflicts among different VNFs towards the network function node (NFV) and provide differentiated service for services in various priorities, a matching-based priorityaware VNF embedding (MPVE) algorithm is proposed to reduce energy consumption while minimizing the total task processing delay. Simulation results demonstrate that MPVE significantly outperforms existing matching algorithm and random matching algorithm in terms of delay and energy consumption while ensuring the task processing requirements of high-priority services.
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Bibliography

[1] Z. Zhou, J. Bai, Z. Sheng, ”A Stackelberg Game Approach for Energy Management in Smart Distribution Systems with Multiple Microgrids”, in IEEE ISADS 2015 workshop on Smart Grid Communications and Networking Technologies. Taiwan, China, 2015.
[2] A. Dadashzade, F. Aminifar, M. Davarpanah, ”Unbalanced Source Detection in Power Distribution Networks by Negative Sequence Apparent Powers”, IEEE Trans. Power Deliv. 36(5), 481-483 (2021).
[3] Z. Lv, W. Xiu, ”Interaction of Edge-Cloud Computing Based on SDN and NFV for Next Generation IoT”, IEEE Internet Things J. 7 (4), 5706-5712 (2020) .
[4] Z. Zhou, X. Chen, B. Gu, ”Multi-Scale Dynamic Allocation of Licensed and Unlicensed Spectrum in Software-Defined HetNets”, IEEE Netw. 33 (6), 9-15 (2019).
[5] G. Wang, S. Zhou, S. Zhang, Z. Niu, X. Shen, ”SFC-Based Service Provisioning for Reconfigurable Space-Air-Ground Integrated Networks”, IEEE J. Sel. Areas Commun. 38 (3), 1478-1489 (2020) .
[6] J. Li, W. Shi, N. Zhang, X. Shen, ”Delay-Aware VNF Scheduling: A Reinforcement Learning Approach With Variable Action Set”, IEEE Trans. Cogn. Commun. Netw. 7 (2), 304-318 (2021).
[7] G. Faraci, G. Schembra, ”An Analytical Model to Design and Manage a Green SDN/NFV CPE Node” IEEE Trans. Netw. Service Manag. 12 (4), 435-450 (2015).
[8] B. R.Al-Kaseem, ”Al-Raweshidy, H.S. SD-NFV as an Energy Efficient Approach for M2M Networks Using Cloud-Based 6LoWPAN Testbed”, IEEE Internet Things J. 4 (2), 1787-1797 (2017).
[9] Z. Zhou, J. Gong, Y. He, Y. Zhang, ”Software Defined Machineto- Machine Communication for Smart Energy Management”, IEEE Commun. Mag. 55(7), 52-60 ( 2017).
[10] C. Mouradian, N. T. Jahromi, R. H.Glitho, ”NFV and SDN-Based Distributed IoT Gateway for Large-Scale Disaster Management”, IEEE Internet Things J., 5 (2), 4119-4131 ( 2018).
[11] L. You, B. Tuncer, R. Zhu, H. Xing, C. Yuen, ”A Synergetic Orchestration of Objects, Data and Services to Enable Smart Cities”, IEEE Internet Things J. 6(2), 10496-10507 ( 2019).
[12] B. Cheng, S. Hou, M.Wang, S. Zhao, J. Chen, ”HSOP: A Hybrid Service Orchestration Platform for Internet-Telephony Networks”, IEEE/ACM Trans. Netw. 28 (5), 1102-1115 (2020).
[13] G. Castellano, F. Esposito, F. Risso, ”A Service-Defined Approach for Orchestration of Heterogeneous Applications in Cloud/Edge Platforms”, IEEE Trans. Netw. Service Manag. 16(3), 1404-1418 (2019).
[14] B. Kar, E. H.-K.Wu, Y. D .Lin, ”Energy cost optimization in dynamic placement of virtualized network function chains”, IEEE Trans. Netw. Service Manag. 15 (4), 372–386 (2018).
[15] M. M.Tajiki, S. Salsano, L. Chiaraviglio, M. Shojafar, B. Akbari, ”Joint Energy Efficient and QoS-Aware Path Allocation and VNF Placement for Service Function Chaining”, IEEE Trans. Netw. Serv. 16 (6), 374-388 (2019) .
[16] L. Ruiz, et al. ”Genetic Algorithm for Holistic VNF-Mapping and Virtual Topology Design”, IEEE Access. 8 (3), 55893-55904 (2020).
[17] K. S. Ghaia, S. Choudhurya, A. Yassineb, ”A stable matching based algorithm to minimize the end-to-end latency of edge nfv”, Procedia Computer Science. 151 (9), 377-384 (2019).
[18] C. Pham, N. H.Tran, C. S. Hong, ”Virtual Network Function Scheduling: A Matching Game Approach”, IEEE Commun. Lett. 22 (5), 69-72 (2018) .
[19] C. Pham, N. H.Tran, S. Ren, W. Saad, C. S. Hong, ”Traffic-Aware and Energy-Efficient vNF Placement for Service Chaining: Joint Sampling and Matching Approach”, IEEE Trans. Serv. Comput. 13 (9), 172-185 (2020).
[20] Z. Zhou et al. Context-Aware Learning-Based Resource Allocation for Ubiquitous Power IoT. IEEE Internet Things Mag. 4(1), 46-52 (2020) .
[21] Z. Zhou, H. Liao, H. Zhao, B. Ai, M. Guizani, ”Reliable Task Offloading for Vehicular Fog Computing Under Information Asymmetry and Information Uncertainty”, IEEE Trans. Veh. Technol.68 (6), 8322-8335 (2019).
[22] Z. Xu, X. Zhang, S. Yu, J. Zhang, ”Energy-Efficient Virtual Network Function Placement in Telecom Networks”, in 2018 IEEE International Conference on Communications (ICC), Kansas City, MO, USA, 2018.
[23] M. C. Luizelli, L. R. Bays, L. S.Buriol, M. P. Barcellos, L. P. Gaspary, ”Piecing together the NFV provisioning puzzle: Efficient placement and chaining of virtual network functions”, in 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM), Ottawa, ON, Canada, 2015.
[24] X. Fei, F. Liu, H. Xu, H. Jin, ”Adaptive VNF Scaling and Flow Routing with Proactive Demand Prediction”, in IEEE INFOCOM 2018 - IEEE Conference on Computer Communications, Honolulu, HI, USA, 2018.
[25] M. Chen, Y. Hao, ”Task Offloading for Mobile Edge Computing in Software Defined Ultra-Dense Network”, IEEE J. Sel. Areas Commun. 36 (2), 587-597 (2018).
[26] D. Yuan, X. Yang, Y. Jiang, Y. Meng, ”An Energy-Delay Trade-Off in Wireless Visual Sensor Networks Based on Two-Sided Matching”, IEEE Sensors J. 19 (6), 10099-10110 (2019).
[27] J. Xu, M. Li, J. Fan, X. Zhao, Z. Chang, ”Self-Learning Super- Resolution Using Convolutional Principal Component Analysis and Random Matching”, IEEE Trans. Multimedia21 (5), 1108-1121 (2018)
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Authors and Affiliations

Xiaoyue Li
1
Xiankai Chen
1
Chaoqun Zhou
1
Zilong Liang
1
Shubo Liu
1
Qiao Yu
1

  1. State Grid Qingdao Power Supply Company, China

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