Distributed Computer and Communication Networks

Future telecommunications networks, going beyond 5G, introduce numerous opportunities for new applications. Increased flexibility implies that new tools and techniques will be needed to take the most out of the networks, as otherwise we will simply create replicas of today’s networks, which potentially include the same bottlenecks. In this keynote, we discuss network topologies, application architectures, and adaptability options that eventually will help in building superior user experience in future telecommunication networks and their applications. This will pave the way towards the Internet of people where technology is simply an enabler for satisfying end-user needs, and technological underpinnings are selected such that they best serve these needs.

In this paper we investigate a sensor network architecture with in-network computation capabilities. The computational tasks are based on numerical calculations, and the parallelization is provided on the lowest, mathematical layer. Since the real network nodes are equipped with atmospheric sensors, we chose a very simple weather prediction model based on the barotropic vorticity equation. To evaluate our network’s capability of producing accurate prediction results, the simulations were executed on a European grid. We used recently measured publicly available data as initial values. Below the results of the distributed calculations are shown.

We model the end-to-end delay of advanced services in the Internet by means of a heavy-tailed Weibull-Pareto distribution (WPD). First we summarize the structural properties of the three-parameter WPD class and indicate its relation to the general Weibull-TX class. Then we present an effective estimation scheme to compute the parameters of a WPD distribution by a finite sample. Finally we show how a WPD distribution can be applied to determine the relevant QoE performance metric MOS of end-to-end delay dependent services in the Internet.

In today’s landscape of utility management, the contribution of Internet of Things (IoT) to smart grids has acquired extensive potential. IoT paves a way to virtually control every smart device in almost every domain of society. Contrariwise, the smart grid networks attracted the attention of the universal research community. The idea of merging IoT with smart grid together demonstrates enormous potential. In this work, we investigate the suitability of Wireless M-BUS communication protocol for possible adoption in remote metering by evaluating possible communication range and system stability in future housing estate represented by university campus made of steel and concrete – this living area acts well when it comes to wireless transmissions. Measurements were executed by means of constructed prototype sensor devices utilizing the frequency 868 MHz which is the frequency by far the most used by WM-BUS devices in Europe.

In this paper we assume that the customers arrive at a single server queueing system according to Markovian Arrival process. When the system is empty, the server goes for vacation and produces inventory for future use during this period. The maximum processed inventory at a stretch is L. The inventory processing time follows phase type distribution. These are required for the service of customers-one for each customer. The server returns from vacation when there are N customers in the system. The service time follows two distinct phase type distributions depending on whether there is processed items or no processed item available at service commencement epoch. We analyse the distributions of time till the number of customers hit N or the inventory level reaches L, idle time, the distribution of time until the number of customers hit N and also the distribution of the number of inventory processed before the arrival of first customer. Also we provide the distribution of a busy cycle, LSTs of busy cycles in which no item is left in the inventory and at least one item is left in the inventory. We perform some numerical experiments to evaluate the expected idle time, standard deviation and coefficient of variation of idle time of the server.

The article presents an approach to the organization of a flying network among mobile communication subscribers based on WiFi (VoWiFi) technology in a disaster area where telecommunication infrastructure is completely or partially destroyed. The flying network is organized on the basis of unmanned aerial vehicles (UAVs), which interact with each other based on IEEE 802.11p wireless technology and with mobile subscribers based on IEEE 802.11n/ac wireless technologies. The interaction process between subscribers and UAVs is presented as a queuing system. Based on the developed model were measured and obtained network delay parameters and its value did not exceed 100 ms. The fulfillment of this condition was achieved by varying the number of UAVs and the channel load parameters. A series of numerical experiments showed the permissible number of UAVs to provide an acceptable quality of voice transmission between subscribers that are in the UAV coverage area.

We propose the new EI-clustering method for random networks. Regarding the underlying graph of a random network, EI-clustering is an advanced statistical tool for community detection and based on the estimation of the extremal index (EI) associated with each node. The EI metric is estimated by samples of indices of the node influences. The latter quantities are determined by the PageRank and a Max-Linear Model. The EI values of both models are estimated by a blocks estimator for each node which is considered as the root of a Thorny Branching Tree. Generations of descendant nodes related to the root node of the tree are used as blocks. The reciprocal of the EI value indicates the average number of influential nodes per generation containing at least one influential node. In the context of random graphs the EI metric indicates the ability of a randomly selected node to attract highly ranked nodes in its orbit. Looking at the changing shape of a plot of the EI metric versus the node number, the node communities are detected. The EI-clustering method is compared with the conductance measure regarding the data set of a real Web graph.

In this paper, we propose and discuss one approach to a data sharing among mobile subscribers. Our idea is to use the identification of wireless networks to simulate some analogue for a peer-to-peer network that will work in the absence of telecommunications infrastructure. A single mobile phone (smartphone) will be sufficient both for creating a node of such telecommunications network and for publishing (disseminating) information. Our proposal is the further development of ideas related to context-aware systems based on network proximity principles. The proposed model allows mobile users to create information hubs directly at the location of the mobile phone of the publisher, which will distribute information for mobile subscribers in the immediate vicinity of it.

Machine-to-Machine (M2M) traffic is growing fast on the Internet, this trend is manifested in the congestion of networks at different levels. The edge cloud unit is used for reducing number of intermediate nodes involved in the communication process and for offloading. The offloading can be seen as three parts. The first is the base station (BS) offloading, as the cloud unit helps the BS in some tasks related to call imitation such as resource allocations. The second is the workload passed from sensor nodes which represents the M2M traffic offloading and the third part is the cellular data offloading. In this paper, we propose an algorithm for offloading the core network using mobile edge computing, which allow devices to exchange traffic with the nearest mobile edge computing for improving QoS and offload channels in the core of the network.

The objective of the paper is to analyzed QoS metric of cloud computing with large-scale of web server from queue management perspective. We propose a new method in order to effectively calculate the steady-state probabilities of cloud system with a large number of web servers. Numerical results showed that the proposed algorithms have higher accuracy and negligible computation time. Taking into account that in the cloud computing repair of server is taking some hours and response time is handling within some seconds, we can correctly apply space-merging algorithm.

The model of asynchronous control procedure of virtual connection of the transport Protocol in the mode of selective failure in the form of a two-dimensional Markov chain with discrete time, taking into account the influence of Protocol parameters window size and the length of the timeout of waiting for end-to-end acknowledgement, the probability of packets distortion in individual links of the data path and queue lengths in transit nodes from the “external” flows onto the bandwidth of the virtual connection. The analysis of the dependence of the throughput of the control procedure on the protocol parameters, the error level in the communication channels, the length of the data transmission path, and the distribution of the queue sizes at the transit nodes.

Integrating information and communication systems into different industries enables storage, management and processing of data and then transforming it into useful information and knowledge. The gradual integration of information technology into beekeeping may provide remarkable results in control over care for bee hives and increase profitability. The aim of this paper is to provide ICT-based means to predict the survival of bee families when the winter season is over. The procedures of collecting and processing of the data from beehives is examined. Several machine learning algorithms are applied and tested. The performance of classification models used for the prediction is estimated. The experimental results are presented.

This paper considers a single server retrial queueing system with search, abandonment and flush out of customers from the system (system clearance) periodically with exponentially distributed duration. A customer on arrival, enters for service, if the server is found to be idle and enter into an orbit of infinite capacity if the server is busy. Orbital customers receive service either by successful retrials or by an orbital search. At the epoch of completion of a service, sever goes for search with probability p as long as the orbit size is atmost L-1. Search stops the moment there are L or more customers in the orbit. Further orbital customers are assumed to renege with certain probability on an unsuccessful retrial. In addition, clearance of system takes place each time a random duration following exponential distribution, expires. The customers arrive to the system according to Markovian arrival Process, inter-retrial times are exponentially distributed and service time follows phase type distribution. We analyze the resulting GI/M/1 Type queue. Steady-state analysis of the model is performed. Some performance measures are evaluated.

For some safety-critical applications, the risk indicator is represented as a time series of estimation errors in the case of a linear model. The safety of the system is compromised if the probability that this risk indicator leaves a given confidence zone at least once during a certain period becomes too important. Sometimes, we are also interested in the calculation of the instantaneous risk probability. The main difficulty is that the Cumulative Distribution Functions (CDFs) (with infinite support) of measurement noise in the above-mentioned linear model are unknown and only their upper and lower bounds are available. The present paper continues the study of previously developed conservative bounds for the above-mentioned risk probabilities as functions of the bounds for the measurement noise CDFs. The original contribution of the present paper consists in the generalization of the previously obtained results to the case of a linear model.

Mobile broadband (MBB) and ubiquitous machine type communications (MTC) appear essential in future 5G networks, however their requirements in terms of data rate, expected number of users, latency and reliability are largely contradictory, which constitutes a major challenge for 5G architecture design. MTC data aggregation via device clustering may prevent signaling congestion due to a massive number of MTC devices in the cell. Resource sharing between MBB and MTC sessions with MTC data aggregation can be modeled using a multi-service loss system, however its numerical analysis is impeded due to the considerable difference in scales of MBB and MTC parameters. In the paper, we use simulation to assess the performance measures of the loss system and its more realistic modification. Cases of light, moderate and heavy MTC loading and various parameters of the MMPP of MTC arrivals are considered.

The article presents the results of the analysis of the need for unification of tethered telecommunication high-altitude platforms (HAP). Possible ways of unification and standardization of HAP, as well as criteria and methods of their structural optimization are considered. It is shown that one of the methods for increasing the efficiency of telecommunication networks is the unification of requirements, component parts and their composite systems. The requirements that should be laid at the stage of setting a technical task for product development are given and it is shown that such parameters as the repeatability factor, the applicability factor, the inter-project unification coefficient are used to assess the level of unification. It is shown that to solve the problems of hardware-software unification and ensure information compatibility, it is necessary to develop appropriate models that take into account the specifics of modern information transmission systems in HAP. The rationale for using the apparatus of logical-dynamic models for solving unification problems is proved, and their joint use with network models allows to formalize the information necessary for solving the problems of hardware-software unification of HAP and ensuring their information compatibility.

In this paper, we discuss cyber-security issues for a digital economy. In particular, this paper targets the complexity of software development for information systems and related problems. This article provides the review of development-related problems for the biggest information systems in the world. We discuss Global Services Management-Operations, DISN, MFSS, and JRSS. This article concentrates on the creation (description) of the system architecture. In our opinion, this is the main issue for large systems. In this connection, the paper discusses the concept of “enterprise architecture” and the framework (model) for Information Systems Architecture proposed by A. Zachman. The main idea of the model is to provide the possibility of the sequential description of each individual aspect of the system in coordination with all the others. Also, we discuss DoDAF metamodel. Any model of enterprise architectures should cover, of course, cyber-security aspects.

The paper presents mathematical model of multi-period inventory management system with stochastic demands and two-switch synchronous control with two thresholds. The control is realized as changing the intensities of the input and output product flows depending on the amount of the accumulated resource in the system. An explicit expression for probability density function of inventory level is found for this system. Also, an example of applying the inventory management models to analysis of cloud computer service is suggested in the paper. Finally, some numerical examples are given to illustrate the obtained results.

We consider a MAP/PH/1 retrial queueing model with orbital search, consisting of a finite number of orbits which are hierarchially ordered. The model consists of an initial orbit of infinite capacity and a finite number, say M finite capacity orbits, each of which is hierarchially numbered according to the number of unsuccessful retrials made by the customers present in them. Each of the M orbits can hold both individually and collectively a maximum of N customers where $$ N \ge M $$ and this results in the loss of customers from the system after each unsuccessful retrial. The server searches for those customers who failed to get service even after making a maximum number, say N retrials. At the end of each service completion epoch, the server searches for customers in orbit $$ _ M $$ with probability p where $$ 0 \le p \le 1 $$ and with its complementary probability $$(1-p)$$ the server remains idle. Search time is assumed to be negligible. Steady state analysis of the system is performed. Some performance measures of the system are evaluated.

A heterogeneous double redundant hot standby renewable system with Marshall-Olkin failure model is considered. In one of previous papers the stationary characteristics for such system for the case of exponential lifetime distributions has been found and its asymptotic insensitivity to the shape of its components repair time distributions has been studied. In this paper the problem of asymptotic insensitivity of such system for both life- and repair time general distributions with the help of simulation method is studied.

The structure of a multidimensional data cube is determined by the aspects of analysis that are used. It is considered as static. If the observed phenomenon changes, the structure of the cube must also be changed. The structure also changes if it is necessary to analyze the data in accordance with the new requirements. In this paper we consider the problem of data reclassification of a multidimensional information system, the results of which should be presented in a cluster form. Cluster description of the structure of a multidimensional data cube is based on identification of groups of members which are connected with groups of members of other dimensions. The use of cluster description allows to identify the semantics of a multidimensional data cube.

The research propose a new approach related to WCA (Weighted Clustering Algorithm) based on a modified method for ad-hoc clustering in wireless sensor networks (WSN). The proposed method include a new functionality for sensor node clustering by including a method for link quality (LQ) prioritization. The method reduce sensitively the risk of crash of the WSN cluster coordinators and help for the energy optimization of the implemented routing protocols.

The model of joint servicing by access node the real time and elastic traffics is proposed. Flows of requests for real time servicing is described by Poisson model (narrowband traffic) or Engset model (broadband traffic). The requests for data transmission are coming by groups according to the Poisson model. Requests from the group occupy free transmission resources or free waiting positions if all transmission resources are occupied. Real time traffic has advantage in occupying the link transmission capacity. It exhibits itself in decreasing if necessary the speed of data transmission to some minimum value. When link has free capacity the speed of data transmission is increasing to some maximum value. The exact and approximate algorithms of estimation the model’s performance measures are suggested. The obtained results can be used for estimation the required transmission capacity of access node for given volumes of offered real time and elastic traffics.

In this paper, we consider an M/GI/GI/1/1 retrial queue where incoming fresh calls arrive at the server according to a Poisson process. Upon arrival, an incoming call either occupies the server if it is idle or joins an orbit if the server is busy. From the orbit, an incoming call retries to occupy the server and behaves the same as a fresh incoming call. After some idle time, the server makes an outgoing call to outside. We consider the system with an unreliable server. In a free state and while servicing outgoing calls the server is reliable and unable to crash. If while servicing an incoming call the server crashes, the incoming call goes into the orbit. The service time of such an interrupted call follows the same distribution as that of an incoming call. For that system we obtained probability distribution of the states of the server, the condition for the existence of a stationary mode and probability distribution of a number of calls in the system.

Earlier we have investigated the discrete-time cyclic-waiting system in the case of geometrically distributed interarrival time and general service time distribution. We obtained the generating functions of ergodic distributions both for the queue length and the waiting time, we got the stability condition in different forms. In this paper we show their coincidence, and find a relation between the zero probabilities for the two models. We also compute the mean values for the queue length and the waiting time.

We consider a single-server retrial queuing system with Markovian Arrival Process (MAP) and phase-type (PH) service time distribution. Customers which find the server busy enter the orbit of infinite size and try their luck after some random time. Concerning the retrial process, we suppose that inter-retrial times have PH distribution if the number of customers in the orbit does not exceed some threshold and have exponential distribution otherwise. Such an assumption allows to some extent take into account the realistic nature of retrial process and, at the same time, to avoid a large increase in the dimensionality of the state space of this process. We consider two different policies of repeated attempts and describe the operation of the system by two different multi-dimensional Markov chains: by quasi-Toeplitz Markov chain in the case of a constant retrial rate and by asymptotically quasi-Toeplitz Markov chain in the case of an infinitely increasing retrial rate. Both chains are successfully analyzed in this paper. We derive the ergodicity condition, calculate the stationary distribution and the main performance measures of the system.

Novel method of the anticollision problem solution in radio frequency identification systems was proposed. It allows to accomplish an unlimited anticollision. The identification of objects is based on using of multiband radio frequency identification tags with time discrete coding, on the introduction of an extended code position, on the application of the multilateration method and the multi-antenna receiving system. The implementation of this method allows the simultaneous identification of an unlimited number of objects, which are marked by radio frequency identification tags, in real time. The method can be implemented in systems using radio frequency identification tags both on surface acoustic waves and on integrated circuits.

The retrial queuing system with general renovation is under investigation. The mechanism of general renovation with retrials means that the packet at the end of its service in accordance with a given probability distribution discards a certain number of other packets from the buffer and itself stays in the system for another round of service, or simply leaves the system without any effect on it. In order to obtain some probability and time related performance characteristics the embedded Markov chain technique is applied. Under the assumption of the existence of a stationary regime, the steady-state probability distribution (for the embedded Markov chain) of the number of packets in the system is obtained, as well as some other characteristics, such as the probability of the accepted task to be served or the probability of the accepted task to be dropped from the buffer, the probability distribution of number of repeated services. Also time characteristics are given.

Predictive modeling is an important part of the monitoring process in cloud computing systems that helps to improve the service availability for the customers. This paper describes two industrial examples of predictive monitoring models for database disk space utilization and Java memory leaks. Practical recommendations are given to improve the forecast accuracy, which can also be used in the other similar cases. The results of this work are validated in the open source monitoring system and are implemented in three big International telecommunications companies.

The generalized negative binomial distribution (GNB) is a new flexible family of discrete distributions that are mixed Poisson laws with the mixing generalized gamma (GG) distributions. This family of discrete distributions is very wide and embraces Poisson distributions, negative binomial distributions, Sichel distributions, Weibull–Poisson distributions and many other types of distributions supplying descriptive statistics with many flexible models. These distributions seem to be very promising for the statistical description of many real phenomena. GG distributions are widely applied in signal and image processing and other practical problems. The statistical estimation of the parameters of GNB and GG distributions is quite complicated. To find estimates, the methods of moments or maximum likelihood can be used as well as two-stage grid EM-algorithms. The paper presents a methodology based on the search for the best distribution using the minimization of $$\ell ^p$$ -distances and $$L^p$$ -metrics for GNB and GG distributions, respectively. This approach, first, allows to obtain parameter estimates without using grid methods and solving systems of nonlinear equations and, second, yields not point estimates as the methods of moments or maximum likelihood do, but the estimate for the density function. In other words, within this approach the set of decisions is not a Euclidean space, but a functional space.

We consider a discrete-time model describing the capital of an input-output system of mixed type. Such models can arise in various applications of probability theory, e.g. queuing and reliability theory, telecommunication, inventories and dams, insurance and many others. The inflow consists of constants, whereas outflow is a sequence of independent identically distributed random variables with a known distribution function. It is also assumed that at the beginning of each period the company under consideration invests a certain quota of the available capital in a non-risky asset for a fixed number of periods. The objective function is the system reliability. Thus, we establish the formula for company ruin probability, in other words, the probability that sooner or later its capital becomes negative. Some numerical results are also provided.

The new types of photonic switching systems based on the newly developed fundamentally new 4x4-switching cell are presented. Using this cell instead well-known 2x2-switching cell allows us to significantly improve the characteristics of switching systems. The double-stage 16x16-switching system and 256x256-switching system are described in detail for the first time. The expressions for the numbers of stages and basic elements on the number of inputs for the developed schemes are obtained for the first time also. Numerical calculations and comparison with well-known schemes is carried out.

Two types of optical smoothly irregular waveguide structures promising for application in optical information systems are studied by numerical simulation and experimentally: the thin film generalised waveguide Luneburg lens and the liquid thin waveguide lens. The importance of the statistical analysis of functioning of optical components in information optical systems is emphasised.

The regenerative methodology is applied to find stability conditions of the so-called N-model which consists of two pools of the interacting servers with two classes of external customers following a renewal input. Service times are assumed to be pool-dependent and, in each pool, are i.i.d. with a general distribution. If the queue size in pool 1 exceeds a given threshold, then a class-1 customer jumps to pool 2 and becomes class-(1,2) customer with the preemptive-resume priority. The stability analysis of this model has been developed in [5] by a modified fluid approach. In addition to the results obtained in work [5], we find the conditions when the 1st pool is stable solely, and when the 1st pool is stable, while the 2nd pool is unstable.

The controllable multiple queuing system (QS) with a switching number of service channels is considered. Such switches are possible at special periodical moments of time (control points) equidistant in time. The intensity of simple input flow at control points randomly changes and these changes ate governed by Markov chain process. It is assumed that during one step (an interval between neighbor control points) QS is in time for a stationary mode. The switching strategy is constructed to maximize a mean one-step profit. Threshold feature of optimal strategy is proved and algorithms for threshold values calculating are derived.

Network Function Virtualization (NFV), Software-Defined Networks (SDN), and Mobile Edge Computing (MEC) are recent technologies that enable new features and functionalities for 5G networks. These technologies are used to provide flexible, scalable and on-demand services for the vast growing array of applications with diverging requirements such low latency, data transmission security, energy efficiency, mobility, massive connectivity, reliability, guaranteed QoS, throughput etc. The introduction of network slicing offers new solutions to manage challenges of application-tailored services in 5G and optimize business model for network operators. In this paper, we present a novel slice-oriented network model and develop a feasible information network demo intended to describe the managerial characteristics and behavior of network slices. The model is mainly depends on the MEC paradigm.

Using of intermediate information storage devices is an important mean to increase the reliability and effectiveness of information system operation. In this paper the semi-Markov model of a single-stream information system with intermediate information storage devices is built. With the aid of phase merging algorithm the stationary characteristics of system operation are approximately found. The analysis of storage devices capacity influence into system characteristics is carried out.

Clustering is a well-known machine learning algorithm which enables the determination of underlying groups in datasets. In electric power systems it has been traditionally utilized for different purposes like defining consumer individual profiles, tariff designs and improving load forecasting. A new age in power systems structure such as smart grids determined the wide investigations of applications and benefits of clustering methods for smart meter data analysis. This paper presents an improvement of energy consumption forecasting methods by performing cluster analysis. For clustering the centroid based method K-means with K-means centroids was used. Various forecasting methods were applied to find the most effective ones with clustering procedure application. Used smart meter data have an hourly measurements of energy consumption time series of russian central region customers. In our computer modeling investigations we have obtained significant improvement due to carrying out the cluster analysis for consumption forecasting.

At present, metric analysis schemes are developed to solve the problems of interpolation, smoothing, extrapolation of multivariable functions and their use for many applied problems [1–7]. In contrast to classical methods and schemes and a majority of other ones [8–20, 23], the metric analysis, like artificial neuron networks, allows reconstructing the studied function values at each specified point of the definition domain separately. The individual position of this point with respect to the ones, where the values of the function are defined, is taken into account. Here we present a review of the published papers on the metric analysis used to solve the above problems, including those under the conditions of uncertainty of the defined values of the studied function. We present recommendations on using the metric analysis schemes and demonstrate the efficiency of the metric analysis methods and schemes.

New optical multicore fibers use their spatial properties in the designs of next-generation systems. To investigate light propagation in such fiber waveguides we use Helmholtz decomposition method.We consider a waveguide having the constant cross-section S with ideally conducting walls. We assume that the filling of waveguide does not change along its axis and is described by the piecewise continuous functions $$\epsilon $$ and $$\mu $$ defined on the waveguide cross section. We show that it is possible to make a substitution, which allows dealing only with continuous functions. Instead of discontinuous cross components of the electromagnetic field $$\varvec{E}$$ and $$\varvec{H}$$ we propose to use four potentials $$u_e, u_h$$ and $$v_e, v_h$$ . Generalizing the Thikhonov-Samarskii theorem, we have proved that any field in the waveguide allows such representation, if we consider the potentials $$u_e, u_h$$ as elements of the Sobolev space and the potentials $$v_e, v_h$$ as elements of the Sobolev space $${W}^1_2(S)$$ .If $$\epsilon $$ and $$\mu $$ are piecewise constant functions, then in terms of four potentials the Maxwell equations reduce to a pair of Helmholtz equations. This fact means that a few dielectric waveguides placed between ideally conducting walls can be described by a scalar boundary problem. This statement offers a new approach to the investigation of spectral properties of waveguides. First, we can prove the completeness of the system of the normal waves in closed waveguides using standard functional spaces. Second, we can propose a new technique for calculating the normal waves using standard finite elements.

Augmented reality application requires both type of data analysis: image recognition or segmentation and appropriate data extracting related to semantic of image. Obtained information matched and provided for end user. The latency is a crucial point, so the fast approaches are mandatory to use. We suggest an approach for combining multiple sources analyses and positioning for augmented reality (AR)-based application. Distinctive features of the method are (1) the use of the coordinates of the observer and camera and the moving object to clarify the position; (2) identification of the object using image recognition and (3) processing of log data obtained from vehicles. The proposed method in this study can be applied in augmented reality-based decision support system which requires obtain and proceed data from multiple data sources. The proposed method was applied to the traffic analysis task based on video streaming and log data analysis where location of observer is the similar to location of camera.

In the paper, the retrial queueing system of M/M/N type with Poisson flow of events and impatient calls is considered. The delay time of calls in the orbit, the calls service time and the impatience time of calls in the system have exponential distribution. Asymptotic analysis method is proposed for the solving problem of finding distribution of the number of calls in the orbit under a system heavy load and long time patience of calls in the orbit condition. The theorem about the Gauss form of the asymptotic probability distribution of the number of calls in the orbit is formulated and proved. Numerical illustrations, results are also given.

A backbone network of road side units (RSUs) is an essential part of modern intelligent transportation systems, where the roadside units are used to collect and distribute information among the mobile users. Connecting each RSU to the data center or Internet is not always feasible due to location and cost constraints. When the RSUs are located close enough to each other, they can be connected via a multihop wireless network where they play a role of the wireless routers. In this paper we consider a partial case when the roadside units are connected in a wireless network with linear topology. Each RSU is equipped with IEEE 802.11 access point that is used by the mobile users to send their data via the network, and with a relay equipment that allows the RSU to connect to the neighbouring RSUs. Each station type is defined by the coverage radius of the access point, connection distance of the relay links and the station price. We also assume that the road has several possible discrete locations where the stations can be deployed. The problem is to find out which stations should be deployed to maximize the overall coverage while providing the given solution cost. First, we formulate the problem in combinatorial form and use this formulation to prove NP-hardness of the problem. Then we define an integer linear program that can be used to find the optimal solution using a well-known software like GLPK or CPLEX.

The need for development of promising tropospheric stations requires the definition of optimal principles for their design and construction. We consider the features of packet transmission with adaptation of operating frequencies in the construction of promising tropospheric stations with a time division duplex, and study the peculiarities of the proposed technical solution. A variant of the basic tactical and technical requirements for prospective types of tropospheric communication stations of various control units of the RF Armed Forces was proposed. The use of systems with a time division duplex when constructing the tactical control tropospheric stations is justified.

The output function recognition of a binary automaton with random Bernoulli input by the character frequency in the output sequence is considered. On the set of output functions, an equivalence relation is introduced, the classes of which consist of functions that are indistinguishable in the scheme. The problem of recognizing the equivalence class of the output function is reduced to the integer optimization problem. Three partial classes of automata close to shift registers are considered.

This paper discusses the application of stochastic Runge-Kutta-like numerical methods with weak and strong convergences for systems of stochastic differential equations in Itô form. At the beginning a brief overview of available publications about stochastic numerical methods and information from the theory of stochastic differential equations are given. Then the difficulties that arise when trying to implement stochastic numerical methods and motivate to use source code generation are described. We discuss some implementation details, such as program languages (Python, Julia) and libraries (Jinja2, Numpy). Also the link to the repository with source code is provided in the article.

Smartbow ear-attached motion active sensor with a 3d accelerometer is used for animal activity tracking. Such technology is required to understand the welfare, nutrition scheme and management strategies for breeding cattle. The ear-tag with integrated sensor has no fixed location and orientation that leads to necessity to use the orientation independent features by solving a time series classification problem. In this paper we propose an accelerometer data transformation techniques based on Euler angle rotation and signal projection and show their equivalence relative to a reference coordinate system. The main aim is to increase a recognition accuracy for the weakly-identified states or actions. The previous research for the fitting of the calves has demonstrated certain difficulties by recognition of some rare states and actions, e.g. milk intake. The results show that an average area under the ROC-curve of 0.740 is achieved with improvement of 0.252 over classifications without data transformation.

This work considers the principles of designing of the new generation of tethered high-altitude telecommunication platforms. A set of theoretical and engineering problems for the development of technology and a system for ground-to-aircraft transmission of high-power energy based on the development of the principle of resonance high-frequency energy transfer by N. Tesla is formulated; of the development of a highly reliable unmanned vehicle for long-term use; of the development of a local navigation system that provides high positioning accuracy and increased noise immunity compared to satellite navigation systems, etc.

Considered system consists of two renewable channels that connected in parallel. The system operates in a random environment having k states. The functioning of both components are described by two continuous time alternating processes. The sojourn time in the state 0 (work state) of both channels has exponential distribution with parameters $$\mu _{1,i}$$ and $$\mu _{2,i}$$ if the random environment has state i. The sojourn times in the state 1 (failed state) have general absolute continuous distributions. These sojourn times are independent and doesn’t depend on the random environment state too. The system is working at time t if at least one channel is working. The system reliability on given time interval is calculated for the known initial states of the components.

Time series forecasting is an attractive and heavily researched area. A very popular approach in this field is the usage of artificial neural networks. Some artificial neural network are oriented to deep learning as training algorithm. In this study instead of hidden layers number extension the size of input layer of tri layers multilayer perceptron is extended. The network starts with 1-1-1 topology. The input layer rise to n, according the size of input time series. In parallel hidden layer goes to m by application of pruning algorithm. Achieved topology n-m-1 is trained with classical backpropagation of the error.