Software & Systems

Articles of journal № 1 at 2022 year.

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1. Time tracking automation for employees working remotely [№1 за 2022 год]
Authors: Shevnina Yu.S., Buravov A.N.
Visitors: 1545
The paper describes a method for solving the problem of time tracking of enterprise employees who work remotely. The method is based on the development of a separate information system with the ability to integrate into the existing project management system. According to surveys made by the IDC research company, the procedure of filling out the time sheet by employees of many companies is ra-ther inconvenient and long. However, in order to manage projects, managers need to know the actual time spent on work. For the server side, the authors used the NestJS framework, for the client web ap-plication – the Angular JS framework. In the process of modeling the information system, diagrams of the time tracking process before au-tomation and after automation were obtained using modern notations for their construction. MS SQL Server has become a relational database management system. The paper presents a comparative analysis of existing solutions for time tracking of enterprise em-ployees, such as: TMetric, StaffCop, WorkPoint, Kickidler, ManicTime, CrocoTime, identifies their main advantages and disadvantages. It also describes the methodology, analysis, selection of develop-ment tools, design and development of an information system that has been successfully implemented in the internal structure of a small enterprise with 70 % of its employees switched to a remote mode of operation. The calculation of the automation equipment efficiency has shown a decrease in the labor intensity of filling out time sheets by 80 % and a 60 % decrease in time costs. Detailed reporting of elapsed time allow more efficient allocation of resources by tasks resulting in increased overall project manageability.

2. An algorithm for ensuring the required level of stability of control of an unmanned aerial vehicle in the conditions of counteraction [№1 за 2022 год]
Author: Belonozhko D.G.
Visitors: 2109
The paper proposes an algorithm for ensuring the required stability level of controlling an unmanned aerial vehicle (UAV) in the conditions of counteraction. It is assumed that the external influence includes both intentional de-structive influences and unintended environmental influences. The sustainable control of UAVs is considered as the ability of the governing bodies to perform their functions in a complex sharply changing environment under conditions of interference, enemy influence (fire, electronic, etc.) and technical failures, keeping the values of all control indicators within the established limits, respectively. The paper considers the means of fire and physical destruction, electronic suppression, as well as means of functional damage by electromagnetic and laser radiation as deliberate destructive environmental influences that threaten to disrupt the stability of UAV control during automatic control. Depending on the probability of defeat-ing a UAV after deliberate destructive influence of the external environment, there are formed zones that charac-terize the influence of influence means on the level of UAV combat capability. The determined acceptable level of stable control probability meets the requirements of a UAV combat-ready state. In order to ensure the required stability level of UAV control, the author used the principle of adaptive control that consists in changing the parameters of the UAV movement to implement the possibility of overflying danger-ous zones. The calculation of the UAV motion control parameters used a mathematical model of the dynamics of the UAV lateral movement. The UAV motion control parameters are formed as a sum of program and corrective control calculated through the required motion parameters of the UAV. The proposed algorithm takes into account the possible intentional destructive impact of the external environ-ment. It can be implemented using microcontrollers of modern UAVs and does not involve making changes to their design. The implementation of the algorithm in UAV automated control systems will effectively solve the tasks of aerial reconnaissance in counteraction conditions to calculate the required motion parameters and to con-trol the UAV corresponding to the current situation.

3. An algorithm of idiom search in program source codes using subtree counting [№1 за 2022 год]
Author: Orlov D.A.
Visitors: 2677
The paper is dedicated to programming idiom extraction algorithm design. Programming idiom is the fragment of source code which often occurs in different programs and used for solving one typical pro-gramming task. In this research the programming idiom is a source code fragment that often occurs in different programs and used for solving one typical programming task. In this research, the program-ming idiom is considered as the part of a program abstract syntax tree (AST), which provides maximum reduce of information quantity in a source code, when all of programming idiom occurrences are re-placed with certain syntax construction (e.g., function call). The developed subtree value metric estimates information amount reduce after such replace. There-fore, the idiom extraction is reduced to search of subtree value function maximum on AST subtree set. To reduce a number of subtrees inspected, the authors use steepest descent method for subtree value function maximum search. At each step subtree is extended with one node, which provides maximum increase of a subtree value metric. Subtrees are stored in a data structure that is a generalization of a trie data structure. The paper proposes an accelerated algorithm of idiom extraction. Programming idiom extraction speedup is achieved through reusing results of idiom efficiency maximum search. The paper also de-scribes the implementation of the developed algorithms. The algorithms are implemented in Python programming language. The implementation extracts programming idioms from source code written in Python. This programming language is chosen due to a large corpus of texts written in such language; it also includes convenient tools for building AST. The authors carried out an idiom extraction experiment using the developed implementation. The idioms were extracted from corpora of an open-source program source code. The extracted program-ming idioms are source code fragments with own meaning. It is also shown that applying developed al-gorithms to a source code of a single software project can reveal possibilities of investigated program refactoring.

4. An analysis of the efficiency of the process of servicing the flow of requests for creating IT-services used a simulation model [№1 за 2022 год]
Authors: Abdаlov A.V., Grishakov V.G., Loginov I.V.
Visitors: 2396
The paper discusses the issues of analyzing the effectiveness of the process of servicing the flow of requests for creating IT services using the simulation modeling method. It shows that the well-known sim- ulation tools do not allow full simulation of the application service process in information and communication in-frastructure administration units characterized by the controlled resource flow nature. The study involved the development of software to simulate the process of servicing the flow of requests for creating IT services. Its main difference was the ability to manage the resource source during the process of servic-ing requests and the possibility of simultaneous experiments on the same source data with several service disci-plines. The simulation model was developed in the Microsoft Visual Studio environment and consists of five mac-roblocks: a request generator, a resource generator, a service device, an algorithm block and an experiment block. The algorithm block allows connecting external models in the form of library blocks that implement the request flow processing through a unified interface, including the ability to generate commands to manage the resource source. The experiment block allows performing streaming experiments based on the specified settings and saved experiment files. The main difference of the developed simulation model is the creation of multiple independent request service flows for various algorithms. The possibility of conducting comparative analysis experiments is illustrated by a se-ries of experiments with stationary and non-stationary request flows and stationary, non-stationary and controlled resource flow based on a family of alternative control algorithms. The results of using a simulation model of the process of servicing requests for creating infocommunication services made it possible to evaluate the effectiveness of the developed promising control algorithms within the framework of the study.

5. Architecture of the software development and testing platform neural network models for creating specialized dictionaries [№1 за 2022 год]
Authors: Purtov D.N., I.G. Sidorkina
Visitors: 2470
The authors propose the implementation of a software platform for creating neural network models with their testing, used to create specialized dictionaries for automated systems. The software platform allows speeding up the process of finding the optimal method for creating a neural network model. The platform is based on an overview of existing tools and methods used to create clock analysis models and software virtualization technologies. A research result is the proposed architecture of a software platform for creating specialized dic-tionaries that ensures the simultaneous creation of different neural network models in virtual contain-ers. A container virtualization of software elements that create and test neural network models provides all mathematical calculations for processing text-based information; decentralized, in parallel and iso-lated training and testing a neural network model. The data exchange between virtual containers, as well as the storage of all the results of the container's operation occurs through a special data bus, which is disk space that all containers have access to. The use of the developed platform can speed up the process of searching for an algorithm for creat-ing specialized dictionaries through testing various hypotheses based on various methods for con-structing models. The process acceleration occurs due to the parallelism and reuse of the mathematical results of the general stages of algorithms whose mathematical calculations were carried out by a simi-lar algorithm. This allows scaling and splitting the learning process not only through the parallel crea-tion of various models, but also at the level of individual model creation stages. The proposed platform was successfully used to find a locally optimal method for creating a model in highly specialized lim-ited-field texts.

6. Intelligent analysis and processing large heterogeneous data for parrying threats in complex distributed systems [№1 за 2022 год]
Authors: Brekotkina E.S. , Pavlov A.S. , S.V. Pavlov , O.I. Khristodulo
Visitors: 2459
The paper proposes a method of intelligent analysis and processing of large heterogeneous data for predicting threats in complex distributed systems. The method is based on the results of automatic monitoring of changes in water level in water bodies and air temperature at the measurement point. Such monitoring makes it possible to increase the efficiency of planning and implementing measures to fend off such and similar threats. The method is based on general approaches and mathematical models previously used by the au-thors to develop adaptive algorithms for controlling gas turbine engines. It is particularly relevant in the context of the increasingly widespread introduction of software and hardware systems for monitor-ing the state of complex distributed systems and the exponential growth in the number of data used to support decision-making. The choice of the future value of the water level at the measurement point is based on the results of processing the data accumulated over all previous flood periods on the compliance of the water level and its changes per day with the values of air temperature and its changes over the same day. The ana-lyzed data are the values of air temperature and water level measured at equidistant points in time, computational values of changes in the water level and air temperature, as well as forecast values (ac-cording to the official data of the hydrometeorological service) of changes in air temperature. Based on the calculation of the retrospective frequency of changes in this temperature and the water level at the corresponding point, it is proposed to choose as the predicted the value that corresponds to the maxi-mum frequency of occurrence of such a combination of measured parameters. The paper presents the results of an experimental assessment of the accuracy of forecasting the wa-ter level in the water bodies of the Republic of Bashkortostan in the flood period of 2021 are. They confirm the applicability of the proposed forecasting method to support decision making to fend off threats in complex distributed systems from a sharp rise in water, even with the current insufficiently automated observation system. With a wider change in highly automated software and hardware com-plexes for monitoring the flood situation, the amount of data analyzed and processed by software sig-nificantly increases, which will complicate the application of traditional methods of data use, and, on the other hand, will increase the efficiency and relevance of the method proposed in this paper.

7. Using job scheduler simulator to evaluate the effectiveness of job run time prediction [№1 за 2022 год]
Authors: Shumilin S.S., Vorobev M.Yu.
Visitors: 1818
The paper investigates the efficiency of queue scheduling using pre-trained models. A supercomputer cluster uses a scheduler to distribute the incoming job flow among the available computing resources. In order to place a job in the queue, the scheduler uses the data specified by a user, including the or-dered program runtime. However, users often misjudge the runtime and choose an upper estimate. If the job completes earlier than specified, then the scheduler needs to reschedule the queue. A large number of such events can reduce the efficiency of resource allocation. Recently, there have been many papers describing the use of machine learning to predict the job run time. This allows using the run time calculated by a pre-trained model during the scheduling process. However, all the models contain an estimation error. Therefore, the problem is the need to assess the efficiency of planning for a given value of the model error. This paper investigates the effectiveness of the proposed approach by comparing the scheduling ef-ficiency in two scenarios: 1) the scheduler uses the time specified by a user and 2) the scheduler uses the real job runtime. For this purpose, the SLURM scheduler simulator performs simulation on the sta-tistical data of the MVS-10P OP2 supercomputer installed at the Joint Supercomputer Center of the Russian Academy of Sciences. The results show that average waiting time in scenario 2 reduced by 25 %. Slowdown reduced by 50 %. Resource utilization did not change significantly. The experimental results indicate the practicability of using machine learning algorithms to predict the running time of jobs arriving at a supercomputer cluster. Thus, the article provides an estimate of the ultimate optimization, since the experiment assumes a hundred percent prediction accuracy, which to date is not demonstrated by any of the presented works on runtime prediction.

8. The adaptive image classification method using reinforcement learning [№1 за 2022 год]
Author: Elizarov A.A.
Visitors: 3241
The paper proposes a method for image classification that uses in addition to a basic neural network for image classification an additional neural network able to adaptively concentrate on the classified im-age object. The task of the additional network is the contextual multi-armed bandit problem, which re-duces to predicting such area on the original image, which is, when cut out of the classification process, will increase the confidence of the basic neural network that the object on the image belongs to the cor-rect class. The additional network is trained using reinforcement learning techniques and strategies for compromising between exploration and research when choosing actions to solve the contextual multi-armed bandit problem. Various experiments were carried out on a subset of the ImageNet-1K dataset to choose a neural network architecture, a reinforcement learning algorithm and a learning exploration strategy. We con-sidered reinforcement learning algorithms such as DQN, REINFORCE and A2C and learning explora-tion strategies such as -greedy, -softmax, -decay-softmax and UCB1 method. Much attention was paid to the description of the experiments performed and the substantiation of the results obtained. The paper proposes application variants of the developed method, which demonstrate an increase in the accuracy of image classification in comparison with the basic ResNet model. It additionally consid-ers the issue of the computational complexity of the developed method.

9. The method for creating parallel software tools for modeling military complexes [№1 за 2022 год]
Author: Aksenov M.A.
Visitors: 2328
Nowadays modeling systems are actively created and used all over the world including the Armed Forces of the Russian Federation. The basis of these systems are modeling complexes, which are a set of technical and software tools providing calculations and imitation modeling. The analysis of modern software tools for modeling military complexes has shown that the duration of the cal-culations performed during imitation largely influence the efficiency of their application when used directly. Specific technological tools used in the development of parallelization of labor-intensive cyclic sections of modeling complexes allow minimizing the time spent on modeling under conditions of limited terms of using software tools. However, nowadays they are not implemented in the general software architecture of modeling complexes accepted for supply in the Armed Forces of the Russian Federation. The paper considers the issues of choosing parallelization algorithms implemented in parallel software devel-opment tools for multi-core (multiprocessor) shared memory computing systems. The purpose of the paper is to assess the impact of the execution time of parallelized cyclic sections of a target program with multithreaded parallel execution of the program in multi-core (multiprocessor) PCs on the results of combat imitation. The scientific novelty is in the development of a new method for creating parallel software tools for modeling military complexes. The paper provides numeric examples of calculations in the Mathcad. To avoid errors in choosing preferred parallelization algorithms, the entire analysis is based on mathematical statistics elements with the probability of a confidence interval for estimating the cycle execution time by a certain algorithm considering the upper limit of the confidence interval. The author proposes a variant of constructing software tools on the example of introduc-ing technological developments into a software architecture of a modeling complex.

10. Modeling an air route network structure with prefractal graphs [№1 за 2022 год]
Author: R.A. Kochkarov
Visitors: 1341
The paper highlights the main research areas: designing a network with given numerical characteristics, calculating the stability of a given network and a solution, solving optimization multicriteria problems with many parameters, and modeling dynamic networks. The structure of networks is hierarchical, with high clustering parameters; it has the properties of self-similarity at the global air transportation level. Air traffic networks are referred as scaleless net-works or “small world” type. Their analysis involves using the theory of complex networks. The au-thors propose the apparatus of prefractal graphs as a tool for solving optimization problems. They also give basic definitions and notations, consider dynamic rules for generating graphs. In order to solve NP-complete problems in transport and logistics systems, it is proposed to use a method that reduces the complexity for a number of subtasks. The paper considers a model for covering an air route network with a prefractal graph, proposes to state a multicriteria problem of locating a multiple center with many weights, and gives a radial metric estimate. There is a proposed algorithm for placing a prefractal graph multiple center while maintaining the adjacency of old edges. Therefore, the authors generate a graph and select the multiple center verti-ces. The rules for generating a prefractal graph make it possible to generate networks with predeter-mined characteristics, such as vertex centrality, diameter, etc., including those for building air routes, locating airports and transfer hubs. The promising directions of further research are the recognition of real aircraft networks in the form of dynamic graphs, weighing by many weights and formulation of optimization multicriterial tasks, analyzing network structural characteristics, a statistical analysis based on small network structural el-ements, generating networks with specified properties and comparing them with real networks, analyz-ing structural stability of networks, etc.

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