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7Paley graphs and Cartesian product for designing promising topologies for networks-on-chip
E. R. Rzaev, A. Yu. Romanov
HSE University
Email: errzaev@edu.hse.ru
DOI 10.24412/cl-35065-2021-1-02-32
The purpose of this work is to study promising network-on-chip (NoC) topologies. Classical NoC topologies
(mesh, ring, torus) are well studied, but their configuration parameters are not the best among all existing
ones. In this work, we study circulant topologies and their modifications, as well as evaluate their parameters
in the context of NoC design. Recently, in a number of works [1, 2], a proposal to use circulant topologies for
designing NoC has appeared. The use of a new topology with better parameters of the diameter and average
distance in comparison with the classical regular topologies made it possible to significantly advance in solving
the problem of finding optimal topological structures. At the same time, the use of circulant topologies has a
number of disadvantages associated with the need to find optimal routing algorithms and avoid deadlocks and
livelocks in the network. There are also other approaches to generating new structures of circulant graphs,
namely, the use of Paley graphs [3] and the direct product of circulant graphs. The result of a study of these
approaches proved their relevance and the need for further research in this direction.
References
1. Monakhova E.A. et al. Analytical Routing Algorithm for Networks-on-Chip with the Three-dimensional Circulant
Topology // 2020 Moscow Work. Electron. Netw. Technol. IEEE, 2020. Art. no. 9067418.
2. Alaei M., Yazdanpanah F. A high-performance FPGA-based multicrossbar prioritized network-on-chip // Concurr.
Comput. John Wiley and Sons Ltd, 2020. P. 2�3.
3. Munir M. et al. Some Invariants of Circulant Graphs // Symmetry (Basel). MDPI AG, 2016. V. 8. No. 11. P. 134.
�o-authorship network structure analysis
N. G. Scherbakova, S. V. Bredikhin
Institute of Computational Mathematics and Mathematical Geophysics SB RAS
Email: scherbakova@sscc.ru
DOI 10.24412/cl-35065-2021-1-02-33
Co-authorship networks of scientists belong to the class of complex networks [1]. Analysis of these net-
works reveals features of academic communities which help in understanding collaborative scientific works
and identifying the notable researchers. A network is defined as follows. The set of co-authorship network�s
nodes consists of authors. There exists an undirected edge between authors u and v iff they produced a joint
paper.
Empirical measurements allow us to uncover the topological measures that characterize the network at a
given moment. The bibliometric data used for this study has been retrieved from the distributed RePEc [2] da-
tabase. We use the simple network model represented by an undirected, unweighted graph. The data was an-
alyzed using statistical techniques in order to get such parameters as the number of papers per author, the
number of authors per paper, the average number of coauthors per author and collaboration indices. We
show that the largest component occupies near 90 % of the network and the degree distribution follows the
scale-free power-law with a small fraction of scientists having a large number of coauthors. An important phe-
nomena of many real networks is the small-worldness. Therefore we investigate two quantities of interest: the
degree of clustering and the average path length and show that the network on study deviates from a random
Erdos � Renyi model [3] of similar size and average connectivity and can be classified as a small world net-
work [4].
This work was carried out under state contract with ICMMG SB RAS (0251-2021-0005)
References
1. Newman M. E. J. Networks: An Introduction. Oxford University Press, 2010.
2. RePEc. General principles. [Electron. res.]. URL: http://repec.org/.
3. Erdos P., Renyi A. On Random Graphs I. // Publ. Math. 1959. V. 6. P. 290�297.
4. Watts D. J., Strogatz S. H. Collective dynamics of 'small-world' networks // Nature. 1998. Vol. 393. P. 440�442.
Decision-making system based on data analysis
L. R. Suleimenova, S. Zh. Rakhmetullina
D. Serikbaev East Kazakhstan technical University, Ust-Kamenogorsk
Email: suleimenovalr@gmail.com
DOI 10.24412/cl-35065-2021-1-02-34
The article is devoted to the analysis of the functional capabilities and future trends of the developed sys-
tem of managing the scientific and educational process based on the analysis of scientometric and academic
data. It also describes the reasons for its creation, the main architectural and technological features, the ser-
vices provided and the prospects for development. The issues of using ontologies for integrating data from
heterogeneous sources and knowledge base organizing are considered. The system is used to test various
evaluation-based decision-making procedures. The main attention is paid to the example of decision-making in
the procedure for appointing teaching staff to positions. The approximate application of the system shows its
analytical advantages as an adaptable tool for the study of a wider range of tasks in scientific and academic
activities. The application of the system shows its analytical advantages as an adaptable tool for the study of a
wider range of tasks in scientific and academic activities. The practical significance and effectiveness of the
system is confirmed by the expanding list of functions that are assigned to it in the field of preparing manage-
ment decisions.
References
1. MacCarthy B.L., Pasley R.C., �Decisions as Units of Organizational Knowledge to Manage Complexity, � in
Information Systems Architecture and Technology: Proceedings of 36th International Conference on Information Systems
Architecture and Technology � ISAT 2015 � Part III. Advances in Intelligent Systems and Computing, vol.431. pp.153-161.
2. Z. Liu, G. Shanshan and S. Yuan, �Research on Teaching Process Management and Quality Monitoring System for
Higher Education, � in 2019 10th International Conference on Information Technology in Medicine and Education (ITME),
Qingdao, China, 2019, pp. 485-489.
3. Bernd Kleimann, Maren Klawitter, "An Analytical Framework for Evaluation-Based Decision-Making Procedures in
Universities" In Theory and Method in Higher Education Research. Published online: 21 Aug 2017; 39-57.
