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Currently, a significant development has been observed in the direction of distributed computing theory, where computational tasks are solved collectively by resource-constrained devices. In practice, this scenario is implemented when processing data in Internet of Things systems, with the aim of reducing system latency and network infrastructure load, as data is processed on edge network computing devices. However, the rapid growth and widespread adoption of IoT systems raise questions about the need to develop methods for reducing the resource intensity of computations. The resource constraints of computing devices pose the following issues regarding the distribution of computational resources: firstly, the necessity to account for the transit cost between different devices solving various tasks; secondly, the necessity to consider the resource cost associated directly with the process of distributing computational resources, which is particularly relevant for groups of autonomous devices such as drones or robots. An analysis of modern publications available in open access demonstrated the absence of proposed models or methods for distributing computational resources that would simultaneously take into account all these factors, making the creation of a new mathematical model for organizing distributed computing in IoT systems and its solution methods topical. This article proposes a novel mathematical model for distributing computational resources along with heuristic optimization methods, providing an integrated approach to implementing distributed computing in IoT systems. A scenario is considered where there exists a leader device within a group that makes decisions concerning the allocation of computational resources, including its own, for distributed task resolution involving information exchanges. It is also assumed that no prior knowledge exists regarding which device will assume the role of leader or the migration paths of computational tasks across devices. Experimental results have shown the effectiveness of using the proposed models and heuristics: achieving up to a 52% reduction in resource costs for solving computational problems while accounting for data transit costs, saving up to 73% of resources through supplementary criteria optimizing task distribution based on minimizing fragment migrations and distances, and decreasing the resource cost of resolving the computational resource distribution problem by up to 28 times with reductions in distribution quality up to 10%.

The effectiveness of communication and data transmission systems (CSiPS), which are an integral part of modern systems in almost any field of science and technology, largely depends on the stability of the frequency of the generated signals. The signals generated in the CSiPD can be considered as processes, the frequency of which changes under the influence of a combination of external influences. Changing the frequency of the signals leads to a decrease in the signal-tonoise ratio (SNR) and, consequently, a deterioration in the characteristics of the signal-to-noise ratio, such as the probability of a bit error and bandwidth. It is most convenient to consider the description of such changes in the frequency of signals as random processes, the apparatus of which is widely used in the construction of mathematical models describing the functioning of systems and devices in various fields of science and technology. Moreover, in many cases, the characteristics of a random process, such as the distribution law, mathematical expectation, and variance, may be unknown or known with errors that do not allow us to obtain estimates of the signal parameters that are acceptable in accuracy. The article proposes an algorithm for solving the problem of determining the characteristics of a random process (signal frequency) based on a set of samples of its frequency, allowing to determine the sample mean, sample variance and the distribution law of frequency deviations in the general population. The basis of this algorithm is the comparison of the values of the observed random process measured over a certain time interval with a set of the same number of random values formed on the basis of model distribution laws. Distribution laws based on mathematical models of these systems and devices or corresponding to similar systems and devices can be considered as model distribution laws. When forming a set of random values for the accepted model distribution law, the sample mean value and variance obtained from the measurement results of the observed random process are used as mathematical expectation and variance. The feature of the algorithm is to compare the measured values of the observed random process ordered in ascending or descending order and the generated sets of values in accordance with the accepted models of distribution laws. The results of mathematical modeling illustrating the application of this algorithm are presented.

Mathematical model of infiltrative tumour growth taking into account transitions between two possible states of malignant cell is investigated. These transitions are considered to depend on oxygen level in a threshold manner: high oxygen concentration allows cell proliferation, while concentration below some critical value induces cell migration. Dependence of infiltrative tumour spreading rate on model parameters has been studied. It is demonstrated that if the level of tissue oxygenation is high, tumour spreading rate remains almost constant; otherwise the spreading rate decreases dramatically with oxygen depletion.

Numerical methods of obtaining collective and one-particle states were used for the quantum description of two-nuclear systems behavior at the initial stage of near-barrier heavy nuclei fusion. The collective exited states in such systems represent concordant oscillations of surfaces of spherical nuclei. The one-particle states of the external neutrons are similar to the states of valence electrons of diatomic molecules.

A mathematical model for the evolution of microbial populations during prolonged cultivation in a chemostat has been constructed. This model generalizes the sequence of the well-known mathematical models of the evolution, in which such factors of the genetic variability were taken into account as chromosomal mutations, mutations in plasmid genes, the horizontal gene transfer, the plasmid loss due to cellular division and others. Liapunov’s function for the generic model of evolution is constructed. The existence proof of bounded, positive invariant and globally attracting set in the state space of the generic mathematical model for the evolution is presented because of the application of La-Salle’s theorem. The analytic description of this set is given. Numerical methods for estimate of the number of limit sets, its location and following investigation in the mathematical models for evolution are discussed.

The paper presents a new dense material modeling method based on spherepolyhedra packing algorithm, describes mathematical model of spherepolyhedra and discuss the results of computation experiments on different spherepolyhedra packs. The results of experiments show convergence of proposed method. Experiments include investigations of spherepolyhedra packs with different shapes, polydisperse and oriented structures. Presented method would be applied to virtual design of dense materials composed of non-spherical particles.

This work considers the problem of optimal control galvanic process in multianode bath. The nonstationary mathematical model of galvanic process, which considers change concentrations of electrolyte components, is developed. Demonstrated rationale for the choice of the form to extremal control on example chrome galvanic process in the standard electrolyte.

In this work, we propose a method of the numerical solution of the magnetostatic problem for domains with boundaries containing corners. With the help of this numerical method, the magnetic systems of rectangular configuration were simulated with high accuracy. In particular, the calculations of some modifications of the magnetic system SP-40 used in the NIS JINR experimental installation, are presented. The basic feature of such a magnet is a rectangular aperture, hence, the area in which the boundary-value problem is solved, has a smooth border everywhere, except for a finite number of angular points in the vicinity of which the border is formed by crossing two smooth curves. In such cases the solution to the problem or derivatives of the solution can have a special feature. A behavior of the magnetic field in the vicinity of an angular point is investigated, and the configuration of the magnet was chosen numerically. The width of the area of homogeneity of the magnetic field increased from 0.5 m up to 1.0 m, i. e. twice.

This article is dedicated to the construction of the approximate mathematical model of the nonlinear elasticity theory for plane strain state. The third order effects method applied to symbolic computing. There three boundary value problems for the first, the second and the third order effects has been obtained within this method, which gets ability to use well-elaborated methods of the linear elasticity theory for the solution of specific problems. This method can be applied for analytical solving of plane problems of nonlinear elasticity theory of stress concentration around holes in mathematical package Maple. Considered example of the triangular hole. The influence of external loads on the stress concentration factor.

At numerical solving of the boundary-value problem of magnetostatic in a domain with a boundary corner point, a question of accuracy of the obtained solution near the corner point of ferromagnetic arises [Zhidkov, Perepelkin, 2001]. Near the corner point an essential growth of the module of the magnetic field can take place, which leads to the necessity of constructing special numerical algorithms when solving the boundary-value problem. This work represents an algorithm of constructing an adaptive mesh in the domain with a boundary corner point of ferromagnetic taking into account the character of behaviour of the solution of the boundary-value problem. An example of calculating a model problem in the domain containing a corner point is given.