Internet of Things, Smart Spaces, and Next Generation Networks and Systems

Exploiting future opportunities and avoiding problematic upcoming events is the main characteristic of a proactively adapting system, leading to several benefits such as uninterrupted and efficient services. In the era when IoT applications are a tangible part of our reality, with interconnected devices almost everywhere, there is potential to leverage the diversity and amount of their generated data in order to act and take proactive decisions in several use cases, smart waste management as such. Our work focuses in devising a system for proactive adaptation of behavior, named ProAdaWM. We propose a reasoning model and system architecture that handles waste collection disruptions due to severe weather in a sustainable and efficient way using decision theory concepts. The proposed approach is validated by implementing a system prototype and conducting a case study.

This paper represents the approach for estimation of the lifetime of the IoT end devices. The novelty of this approach is in the taking into account not only the energy consumption for data transmission, but also for ensuring the security by using the encryption algorithms. The results of the study showed the effect of using data encryption during transmission on the device lifetime depending on the key length and the principles of the algorithm used.

Edge computing is currently one of the main research topics in the field of Internet of Things. Edge computing requires lightweight and computationally simple algorithms for sensor data analytics. Sensing edge devices are often battery powered and have a wireless connection. In designing edge devices the energy efficiency needs to be taken into account. Pre-processing the data locally in the edge device reduces the amount of data and thus decreases the energy consumption of wireless data transmission. Sensor data compression algorithms presented in this paper are mainly based on data linearity. Microclimate data is near linear in short time window and thus simple linear approximation based compression algorithms can achieve rather good compression ratios with low computational complexity. Using these kind of simple compression algorithms can significantly improve the battery and thus the edge device lifetime. In this paper linear approximation based compression algorithms are tested to compress microclimate data.

The current challenges of many mobility solutions are based on an extremely fragmented booking system with complex service layers. A cross-company and user-friendly exchange of information and offers from different mobility providers is often not possible. Against this background, Distributed Ledger Technology (DLT) has the potential to revolutionize the existing mobility sector and enable completely new business models. Thus, we present a distributed mobility platform, which is valuable for a variety of mobility services. In contrast to conventional platform approaches, the data management of our infrastructure is distributed, transparent, and cost-efficient. By prototypically implementing the concept, we can demonstrate its technical feasibility and at the same time demonstrate that the introduction of our distributed mobility concept will benefit both the supply and demand sides of public transportation.

There has been a growing interest in adopting ontologies to address semantic interoperability in the domain of Internet of Things (IoT). Recent research claims that the lack of semantic interoperability support in IoT infrastructures hinders the potential of IoT for offering large scale value-added services. This article explores this fundamental issue through a systematic mapping of literature. The mapping intends to answer a set of research questions and identifies research gaps and trends that will guide future research in IoT semantic interoperability modeling.

Internet of Things devices have seen a rapid growth and popularity in recent years with many more ordinary devices gaining network capability and becoming part of the ever growing IoT network. With this exponential growth and the limitation of resources, it is becoming increasingly harder to protect against security threats such as malware due to its evolving faster than the defence mechanisms can handle with. The traditional security systems are not able to detect unknown malware as they use signature-based methods. In this paper, we aim to address this issue by introducing a novel IoT malware traffic analysis approach using neural network and binary visualisation. The prime motivation of the proposed approach is to faster detect and classify new malware (zero-day malware). The experiment results show that our method can satisfy the accuracy requirement of practical application.

Predicting the time and place where concentrations of pollutants will be the highest is critical for air quality monitoring- and early-warning systems in urban areas. Much of the research effort in this area is focused only on improving air pollution prediction algorithms, disregarding valuable environmental- and user-based context. In this paper we apply context-aware computing concepts in the MyAQI system, to develop an integral air quality monitoring and prediction application, that shifts the focus towards the individual needs of each end-user, without neglecting the benefits of the latest air pollution forecasting algorithms. We design and describe a novel context and situation reasoning model, that considers external environmental context, along with user based attributes, to feed into the prediction model. We demonstrate the adaptability and customizability of the design and the accuracy of the prediction technique in the implementation of the responsive MyAQI web application. We test the implementation with different user profiles and show the results of the system’s adaptation. We demonstrate the prediction model’s accuracy, when using extended context for 4 air quality monitoring stations in the Melbourne Region in Victoria, Australia.

This article describes an approach to parallelizing of data mining algorithms in logical programming framework, for distributed data processing in cluster. As an example Naive Bayes algorithm implementation in Prolog framework, its conversion into parallel type and execution on cluster with MPI system are described.

This paper considers the issues of ensuring the cybersecurity of autonomous objects. Prerequisites that determine the application of additional independent methods for assessing the state of autonomous objects were identified. Side channels were described, which enable the monitoring of the state of individual objects. A transition graph was proposed to show the current state of the object based on data from side channels. The type of sound signals used to analyze and classify the state of information security was also shown. An experiment intended to accumulate statistical information on the various types of unmanned object maneuvers was conducted using two audio recorders. The data obtained was processed using two-layer feed-forward neural networks with sigmoid hidden neurons. The autonomous object behavior model can be used as an additional element to determine the state of cybersecurity. Using a segmented model, it was possible to improve the accuracy of determining the cybersecurity state. The proposed model enabled the identification of differences in the states of autonomous object cybersecurity with probabilities that were, on average, more than 0.8.

The paper discusses a novel class of decision support systems, based on an environment, leveraging human-machine collective intelligence. The distinctive feature of the proposed environment is support for natural self-organization processes in the community of participants. Most of the existing approaches for leveraging human expertise in a computing system rely on a pre-defined rigid workflow specification, and those very few systems that try to overcome this limitation sidestep current body of knowledge of self-organization in artificial and natural systems. The paper outlines the general vision of the proposed environment, identifies main challenges that has to be dealt with in order to develop such environment and describes ways to address them. Potential applications of such decision support environment are ubiquitous and influence virtually all areas of human activities, especially in complex domains: business management, environment problems, and government decisions.

Facebook represents the current de-facto choice for social media, changing the nature of social relationships. The increasing amount of personal information that runs through this platform publicly exposes user behaviour and social trends, allowing aggregation of data through conventional intelligence collection techniques such as OSINT (Open Source Intelligence). In this paper, we propose a new method to detect and diagnose variations in overall Facebook user psychology through Open Source Intelligence (OSINT) and machine learning techniques. We are aggregating the spectrum of user sentiments and views by using N-Games charts, which exhibit noticeable variations over time, validated through long term collection. We postulate that the proposed approach can be used by security organisations to understand and evaluate the user psychology, then use the information to predict insider threats or prevent insider attacks.

The system of streaming data and complex events distributed processing is considered. A mathematical model for computational resource consumption and allocation in edge computing is offered. On the basis of mathematical model there was developed a multi-agent algorithm as a part of agent-based software architecture for distributed processing of streaming data, which had been developed by the authors previously. The efficiency of the developed algorithm has been investigated by means of simulation in AnyLogic. The resource allocation problem in edge computing was simulated and the algorithm demonstrated satisfying results both at static and dynamic regimes. Also, the perspectives of intellectual technologies using in resource allocation for edge computing are considered.

This article describes the results of applying a context-based approach to modelling when building a conditional system to counter fraud in transport. In this application, the exploration of the subject area into three contexts aimed at describing the characteristics of the driver’s behaviour, his basic habits and the search for global anomalies based on historical data is considered The relationship and influence of context states is described by the system of the expert tree described. The description of the approach describes the advantages of the context-based approach when modelling analytical systems. At the end of the article, the results of testing the conditional system on synthetic data obtained from the collection of telematics data on the location and linear acceleration using a mobile device are described. It is shown that the proposed approach allows the detection of fraudulent actions of a telematics service user in more than 98% of cases with 16% of false positives.

Analysis of the vehicles’ movement on the territory of the organization represents an area of considerable interest for both cyber-physical security and financial applications. In the paper an approach to the analysis of the vehicles routes on the territory of the organization is presented. The vehicle route is reconstructed on the basis of the data from different sources such as access control system, video surveillance and weight measuring devices. The approach presented consists of two stages: exploratory analysis of the data that allows constructing analysis models for detection deviations in the vehicle movement in the real time mode; and analysis of the sensor readings in the real time mode. We tested our data on both artificial data and real world data.

Future cyber operations in an IoT-enabled smart environment will be much more demanding and complex. The purpose of this paper is to present the building blocks of an innovative approach to education in the field of cyber operations. Proposed model of an innovative approach to education in the field of cyber operations includes three building blocks with the set of key elements. The model is focused on the work process of cyber operations modelling, that will allow students with different levels of knowledge and specializations to work efficiently. The objective of the innovative approach to education in the field of cyber operations is to connect students with different knowledge in the field of cyber security and thus contribute to the development of highly secure IoT solutions and better security awareness. The main objective of the proposed model of an innovative approach to education in the field of cyber operations is to allow the students to develop a content-rich, in-depth knowledge in the field of cyber operations, especially in smart environment.

In this paper, we target the strategy for telecommunications architectures during the transition to the IP-only models. The paper discusses the shifting from circuit switching to packet switching in telecommunications. Particularly, we analyze the coexistence of circuit switching and packet switching technologies in American military communications where each warfare object should have own IP address. The paper discusses the role of multifunction Soft Switches (MFSS). This Soft Switch plays the role of a media gateway between TDM channels and IP channels. As a case, we are passing through the transformation from SS7 signaling to internet protocol, ISDN-based government Defense Red Switch Network and, finally, the extremely ambitious cybersecurity issues and the cyber vulnerabilities of weapons found by Government Accountability Office. We conclude the growing cyber threats will provide a long-term channel-packet coexistence.

Wireless sensor networks function as one of the enablers for the large-scale deployment of Internet of Things in various applications, including critical infrastructure. However, the open communications environment of wireless systems, immature technologies and the inherent limitations of sensor nodes make wireless sensor networks an attractive target to malicious activities. The main contributions of this review include describing the true nature of wireless sensor networks through their characteristics and security threats as well as reflecting them to network anomaly detection by surveying recent studies in the field. The potential and feasibility of graph-based deep learning for detecting anomalies in these networks are also explored. Finally, some remarks on modelling anomaly detection methods, using appropriate datasets for validation purposes and interpreting complex machine learning models are given.

Rapid growth of radio emission sources (RES) leads to the interference of signals from various transceivers and thus complicates its positioning based on direction finding (DF). Traditional DF use structural-statistical redundancy to resolve multi-signal and multipath situations, which makes impossible to implement it in compact direction finders. The aim of current work is to investigate possibilities of polarization DF accounting interference conditions. It is proposed to use frequency and phase differences of received rays in the interference mixture of signals in tri-orthogonal antenna system (TOAS). The solution to polarization DF task of RES during interference utilize methods of search for normals to planes that are envelopes from a family of curves, which use the resultant field, induced in TOAS. The novelty of presented solution is in the realization of the idea that in the case of RES interference with frequency or phase differences in TOAS, the resulting field vector forms three-dimensional shape, which contains spatial parameters of the rays. Contribution of current investigation validates the use of relatively simple DF techniques in a complex interference environment, both for several sources and separation of rays from one source.

Expansion of modern wireless communication technologies have led to spectrum scarcity due to inefficient spectrum utilization by conventional TV broadcasting technologies. While the transition of television from analogue to digital leaves an unused spectrum aka white space (WS). A need for a sophisticated coexistence mechanism observe to enable smooth operation of unlicensed secondary systems in TVWS sub-one-gigahertz (Sub-1GHz). To that end, this paper proposes a two-step algorithm to enables an efficient coexistence mechanism among cells in TVWS. This approach assumes a WS geo-location database (WSDB) as central entity allowing a new cell to operate in a given geographic area. When a new cell query is sent to WSDB, it ensures that the new cell will not overlap with already-deployed cells. This enables the cells to be in coexistence with neighbouring cells without interfering each other transmissions. Simulation results show that the proposed algorithm enables enhanced performance gains in terms of cell density and area capacity. The required cell density is notably increased in a given geographic area leading to improved area capacity while it also ensures the efficient TVWS utilization among cells.

LoRaWAN represents a promising Internet of things (IoT) technology that has recently gained high a market and academic interest. With the recent advances in sensory manufacturing, the number of connected devices increases dramatically and thus, a reliable IoT system able to provide the coverage for such system becomes a high demand. This paper proposed a reliable LoRaWAN architecture for ultra-dense IoT networks. The mobile edge computing is proposed to provide the computing and energy resources at the edge of the access LoRa network, while the software defined networking (SDN) is deployed at the core network to manage and control the whole network traffic. The novelty of the proposed system comes from the deploying of a distributed version of the SDN controller at the edge servers, to reduce the load on the core network. The system is simulated for various simulation scenarios and the results validate the proposed structure for ultra-dense and ultra-low latency IoT networks.

With the dramatic increase in the number of connected devices, the traffic generated by these devices puts high constraints on the design of fifth generation cellular systems (5G) and future networks. Furthermore, other requirements such as the mobility, reliability, scalability and quality of service (QoS) should be considered as well, while designing such networks. To achieve the announced requirements of the 5G systems and overcome the high traffic density problems, new technologies, such as the mobile edge computing (MEC) and software defined networking (SDN), and novel schemes, such as artificial intelligence (AI) algorithms and offloading algorithms, should be introduced. One main issue with the 5G networks is the heterogeneous traffic, since there are enormous number of applications and sub-networks. The main design challenge with the 5G network traffic is the recognition and classification of heterogeneous massive traffic, which cannot be performed by the current traditional methods. Instead, new reliable methods based on AI should be introduced. To this end, this work considers the problem of traffic recognition, controlling and management; mainly for ultra-dense 5G networks. In this paper, a novel AI algorithm is developed to detect and recognize the heterogeneous traffic at the core network. The algorithm is implemented at the control plane of the SDN network, located at the core network. The algorithm is based on the neural network. The system is simulated over a reliable environment for various considered cases and results are indicated.

In this paper we consider the problem of maintaining communication between a transmitter and a receiver in the presence of hostile interference. To maintain communication the transmitter must keep the SINR greater or equal to an SINR threshold, while the adversary aims to break the communication by making this SINR less than this threshold. In particular, we focus on investigating how incomplete information about the adversary’s location can impact the rival’s strategies. Namely, we assume that the transmitter does not know the adversary’s location, but knows only an a priori distribution of possible adversary locations. The problem is formulated as a non-zero Bayesian game between the transmitter and the adversary in a Nash and Stackelberg framework for Rayleigh channel fading gains. Existence and uniqueness of both type of equilibria are proven and derived in closed form. We prove theoretically, and numerically illustrate, that the Stackelberg equilibrium strategy for the transmitter can be non-sensitive to the a priori information, while the Nash equilibrium strategy for the transmitter is always sensitive to such information. The condition when the Stackelberg transmitter equilibrium strategy is non-sensitive to a priori information is derived.

In the wake of recent hardware developments, augmented, mixed, and virtual reality applications – grouped under an umbrella term of eXtended reality (XR) – are believed to have a transformative effect on customer experience. Among many XR use cases, of particular interest are crowded commuting scenarios, in which passengers are involved in in-bus/in-train entertainment, e.g., high-quality video or 3D hologram streaming and AR/VR gaming. In the case of a city bus, the number of commuting users during the busy hours may exceed forty, and, hence, could pose far higher traffic demands than the existing microwave technologies can support. Consequently, the carrier candidate for XR hardware should be sought in the millimeter-wave (mmWave) spectrum; however, the use of mmWave cellular frequencies may appear impractical due to the severe attenuation or blockage by the modern metal coating of the glass. As a result, intra-vehicle deployment of unlicensed mmWave access points becomes the most promising solution for bandwidth-hungry XR devices. In this paper, we present the calibrated results of shooting-and-bouncing ray simulation at 60 GHz for the bus interior. We analyze the delay and angular spread, estimate the parameters of the Saleh-Valenzuela channel model, and draw important practical conclusions regarding the intra-vehicle propagation at 60 GHz.

In millimeter-wave (mmWave) networks, where faster signal attenuation is compensated by the use of highly directional antennas, the effects of high mobility may seriously harm the link quality and, hence, the overall system performance. In this paper, we study the channel access in unlicensed mmWave networks with mobile clients, with particular emphasis on initial beamforming training and beam refinement protocol as per IEEE 802.11ad/ay standard. We explicitly model beamforming procedures and corresponding overhead for directional mmWave antennas and provide a method for maximizing the average data rate over the variable length of the 802.11ad/ay beacon interval in different mobility scenarios. We illustrate the impact of the client speed and mobility patterns by examples of three variations of the discrete random walk mobility model.

Threshold (k, n)-schemes are applied to ensure fault tolerance in many protocols of distributed computing, where k is a minimum amount of nodes and $$n \ge k$$ is a total number of nodes in the system. When $$n=k$$ in such a system, if one of the nodes fails during the execution of this protocol, it is replaced with a new one and the procedure is restarted, while all the time and traffic spent during the previous stages will be lost. If it is initially involved more than the minimum threshold of nodes ( $$n > k$$ ), then in case of any node fails, the protocol will not be restarted. In such a case, an optimization problem arises, which consists in runtime minimizing of the protocol with given constraints on the threshold k and the failure characteristics. In this paper, using the example of the threshold calculation protocol of the digital digest, such an optimization problem will be formulated and solved.

A single-server priority queuing system with limited buffer size, Poisson arrivals, an exponentially distributed service time is considered. The primary customers take preemptive priority over secondary customers. We also consider a randomized push-out mechanism. It allows pushing secondary customers out of the system to free up space that could be taken by primary customers. Studied a new model where in addition to mentioned above two kinds of regular arriving customers, there are negative arrivals. A negative arrival has the effect of removing a customer from the buffer. The type of customer to be removed is determined in accordance with the following kill strategy. If at the moment of the occurrence of the next negative customer, both types of positive customers were presented in the system, then the primary customer is getting removed with a given probability. If there is only one type of customers in the system, then the customer of the existing type is deleted. Finally, if the system does not contain any positive customers at all, then a negative customer does not affect it. It is shown that such a queuing system can be investigated using the technique developed earlier by the authors for similar systems without negative customers. Using the method of generating functions, loss probabilities for both types of positive customers are obtained. The dependence of these loss probabilities on the basic parameters of the model (such as the probability of pushing out and the probability of crowding out a positive customer by a negative one) is investigated.

Nowadays, the number of mobile subscribers has increased significantly. It is predicted that the number of subscribers will reach 9.5 billion by 2020. With such rapid growth, telecommunications networks suffer from several problems, such as lack of bandwidth, the occurrence of collisions and interference. To cope with the problems, it was proposed to fill the lack of the licensed spectrum with an unlicensed frequency bands. However with this approach, it is necessary to provide fair coexistence in the unlicensed band with existing users. The use of LTE - LAA technology is designed to solve this problem. The paper builds an analytical model of the LAA work scheme using a discrete time Markov process, which provides a probabilistic estimate of the collision and data transmission probabilities. This work also outlines all the principles and specifications necessary to describe the functioning of the model. A description of the LBT mechanism for the unlicensed spectrum is given. After analytically obtained expressions for collision and transmission probabilities, numerical results are presented.

ITU-R requirements related to technical performance for IMT-2020 radio interfaces claims average spectral efficiency (SE) up to 9 bit/s/Hz for indoor hotspot, 7.8 bit/s/Hz for dense urban and 3.3 bit/s/Hz for rural environment. The purpose of this work is to analyse the performance of beamforming signal processing techniques for various massive MIMO configurations in terms of SE and reveal scenarios, which meet ITU-R requirements. Analysis is performed for single user (SU) and multi-user (MU) cases with 14, 50, 100 users, various number of antenna ports (8, 32, 64 and 128) and three beamforming techniques: matched filter (MF), minimum mean square error (MMSE) and zero-forcing (ZF). Simulation results compare SE as a function of signal-to-noise ratio (SNR) for various beamforming techniques and conclude that at higher SNR MMSE acts as ZF and at low SNR MMSE acts as MF for the case, when the number of users is much lower than the number of antenna ports. MU case analysis reveal, that ITU-R average SE requirements hold only in rural environment for high SNR values and 128 antenna ports.

The number of Unmanned Aerial Vehicle (UAV) applications is growing tremendously. The most critical ones are operations in use cases such as natural disasters, and search and rescue activities. Many of these operations are performed on water scenarios. A standalone niche covering autonomous UAV operation is thus becoming increasingly important. One of the crucial parts of mentioned operations is a technology capable to land an autonomous UAV on a moving surface vessel. This approach could not be entirely possible without precise UAV positioning. However, conventional strategies that rely on satellite localization may not always be reliable, due to scenario specifics. Therefore, the development of an independent precise landing technology is essential. In this paper, we developed the localization and landing system based on Gauss-Newton’s method, which allows to achieve the required localization accuracy.

An algorithm is considered for estimating speeds and distances to targets in the multi-target mode as applied to the linear frequency modulation continuous wave (FMCW) car radar of a millimeter-wave range. The algorithm is based on an estimate of the fast Fourier transform (FFT) amplitude spectrum of the received microwave signals. The reasons for the occurrence of false targets when using frequency modulation continuous wave radars and the probability of their occurrence are identified. Using a computer experiment in the LabVIEW environment, the detection efficiency in additive white noise was investigated and the probability of detection was calculated for various ratios signal to the noise at the radar receiver input.

Determining the state of each cell, for instance, cell outages, in a densely deployed cellular network is a difficult problem. Several prior studies have used minimization of drive test (MDT) reports to detect cell outages. In this paper, we propose a two step process. First, using the MDT reports, we estimate the serving base station’s transmit power for each user. Second, we learn summary statistics of estimated transmit power for various networks states and use these to classify the network state on test data. Our approach is able to achieve an accuracy of 96% on an NS-3 simulation dataset. Decision tree, random forest and SVM classifiers were able to achieve a classification accuracy of 72.3%, 76.52% and 77.48%, respectively .

5G new radio millimeter wave (5G NR mmWave) is the upcoming technology with a new interface which is developed to be an extension to the existing 4G technology. The main target for 5G is to have a wide range of services with the high data rate, high coverage, reduced delay, reduced cost, high system capacity and multiple connectivity for users everywhere. In this paper, a performance study of 5G cell in the downlink is considered. The main idea of 5G is to provide high performance regarding throughput and spectral efficiency in the dense urban area which is not possible to be provided by a Wi-Fi network. Based on OFDM modulation, the 5G cell is divided into three virtual zones to study the performance of 5G in the inner zone compared to outer zones for licensed and unlicensed spectrum alike. Different performance indicators are considered in the analysis such as; loss probability, delay, throughput as well as aggregate average bit rate in different zones. The provided numerical results show that 5G performance is always better in the most inner zones (i.e. pico) compared to the outer zones (i.e. micro and macro) zones, consequently, the overall cell performance is also improved. Besides, 5G performance is compared with LTE performance under the same simulation parameters to show that 5G always provide a better performance, especially in the most inner zone.

The authors in [9] introduced basic concept of delta-orthogonal multiple access (D-OMA) scheme. This scheme for massive wireless connectivity in wireless communications allows the implementation of 6G cellular networks. The practical implementation of 6G cellular networks requires solving many problems, including downlink power allocation of all multiple access points (APs). In this paper, an optimal downlink power allocation model is developed. To overcome the substantial computational complexity of the power allocation optimisation approach, a heuristic algorithm based on the Stackelberg game was proposed. The theoretical results were confirmed by simulation.

Vehicular ad hoc network (VANET) can manage live traffic and send emergency messages to the base station in any smart city and is emerging as a connectivity network. In VANET, every vehicle acts as a sensor node, which collects the surrounding information and sends information to the base station. VANET network is created when communication between cars with wireless transceiver is needed. Despite the fact that VANET and mobile ad hoc network (MANET) have some similarities; the dynamic nature of VANET has posed a challenge on routing protocols designing; VANET is composed of models based communication among vehicles and vehicle with a high mobility feature. Presently the artificial neural networks is often used in several fields. Neural networks are usually trained by conventional backpropagation learning algorithm that minimizes the training data mean square error (MSE). The goal of this paper is to investigate VANET performance in terms of packet loss rate and throughput using robust neural networks learning based on the robust M-Estimators performance function instead of the traditional MSE performance function. Robust M-estimators performance functions outperform the traditional MSE performance function in terms of RMSE and training speed as simulation results show.

Latency is an important metric of mobile applications performance. To reduce the latency, recently it was proposed to replace the standard centralized architecture of mobile applications by the mobile edge computing (MEC). Such an approach allows processing of users data closer to their location. Motivated by disaster response scenarios, in this paper we investigated the capabilities of MEC for the forwarding of first aid request as an illustrative example of P2P service discovery in an emergency situation. We proposed an analytical model of the system and executed performance evaluation using system level simulator. Our results show that the developed solution considerably reduces the request processing time. The proposed solution can be used not only for first aid but also for general purposes, e.g., searching various service providers in a certain location.

Increasing amount of attacks and intrusions against networked systems and data networks requires sensor capability. Data in modern networks, including the Internet, is often encrypted, making classical traffic analysis complicated. In this study, we detect anomalies from encrypted network traffic by developing an anomaly based network intrusion detection system applying neural networks based on the WaveNet architecture. Implementation was tested using dataset collected from a large annual national cyber security exercise. Dataset included both legitimate and malicious traffic containing modern, complex attacks and intrusions. The performance results indicated that our model is suitable for detecting encrypted malicious traffic from the datasets.

In this paper, we discuss steganographic methods LSB, F5, and WF5 for embedding information into a container to enable copyright protection. We analyze the difference between selected methods and show how to decrease the container distortion by dividing codewords into several zones of significance using perfect codes in the weighted Hamming metric. Additionally, we propose a number of variants for different container types and test some parameters on several images.

This paper presents some results of the routing task formulation and solving for the software defined networks. We consider the routing task as search of the optimal path and the task of the resources distribution. Choosing of the path search method affects on the network resources utilization and quality of service. We consider this task as the optimization problem and consider the objective functions forming in the points of view of both of the tasks. Some examples of solutions were obtained by using of simulation method. Analysis of these results shows difference between the different approaches for the objective function formulation.

As the health, social services and regional government reform set great expectations for the new technology and the savings it brings, the importance of cyber security increases. When training cyber security for the personnel of the South Ostrobothnia Hospital District (EPSHP), the shortcomings in cyber security awareness emerged. Because improving the awareness is the easiest, fastest and cheapest way to improve cyber security level in organizations, the current level of cyber security awareness was seen valuable to measure in organizations under the reform in the region of South Ostrobothnia.The study investigated the current level of cyber security awareness and the reasons affecting it. Cyber security awareness studied with three different surveys. The first two surveys organized as a part of cyber security lessons for the personnel of the Hospital District of South Ostrobothnia. The third survey conducted as an internet survey for all organizations involved in the reform in South Ostrobothnia. A total of over 1,200 responses to the questionnaires analyzed using material-based content analysis. The results enabled to create an overall view of the current level of cyber security awareness in the organizations, the coverage of the education and the reasons affecting them.According the results, the cyber security awareness and education are lacking among the personnel and management in the target organization. The overall cyber security awareness should be improved in all target organizations.

Internet of things represents the third generation of the Internet that is expected to connect billions of heterogeneous devices in a smart way. This large number of connected devices puts high constraints on the system structure and design. In this paper we analyze the features of the IoT networking. The aim of this paper is the Internet of Things organization, as well as the modeling of the message delivery process in conditions of low density of users and in case of low mobile networks coverage. The target network is considered as a network with moving nodes that can perform the functions of data transporting between points with different geographic coordinates. A proposed system in this paper allows to implement an approach for building of such network.

We developed the mechanism of assessing cyber risks for Internet of Things (IoT) projects. The relevance of this topic is explained by growing sophistication of cyber-attacks, the speed of new threats emergence and increasing damage from the attacks. The paper addresses decreasing efficiencies of existing mechanisms of cyber risk assessment and fills the research gaps in this area. Results include development of the mechanism’s concept, its block diagram, the specification and description of its comprising tools and the case study. Unlike peers, the mechanism provided holistic approach to cyber risk assessment; integrated and coordinated all related activities and tools. It simulated the confidence interval of project return on investments (ROI) and showing the chances to go above risk appetite. It makes cyber risk assessment dynamic, iterative, responsive to changes in cyber environment. These advantages let us conclude that the mechanism should have a significant scientific and practical use.

The Authors have analyzed features of mobile virtual network operators (MVNO) building following levels: high, low and reseller for different business model taking into account utilization new technological and architectural possibilities of 5G networks. During the research work topology and structure of MVNO high level based on 5G network functions were designed. The proposed structure of MVNO based on sharing 5G network resource: 5G MOCN (5G Multi-Operator Core Network) и 5G GWCN (5G Gateway Core Network). In the aim of seamless radio coverage realization by multi standard access network were considered issues of MVNO-network integration with base stations 4G/5G. Joint utilization of numeration and addressing for mobile network operator (MNO) and High level MVNO were systematized in the article. The principles of search and selection by a subscriber device of a network of a high-level virtual mobile operator, the principle of selecting network functions (NF Select) depending on network slices are considered.

We have analyzed the market of infocommunication services in Russia. The number of both mobile Internet users and fixed-line Internet subscribers increased in 2011–2017. In 2017, mobile Internet in Russia was used by 124.83 million people, which is 7.7% higher than in 2016, and 47.7% higher than in 2011; 93% of mobile Internet subscribers are users of broadband Internet access with a declared speed of 256 Kbps. However, even though mobile operators still have large revenues from mobile communications, no serious revenue increase can be reported in the sector. For this reason, Russian telecom companies are beginning to follow the path of digital development, namely, developing financial services, system integration, e-commerce and the Internet of things. Active development of this line of business in the near future will lead to a decrease in the share of telecom services in the revenues, but mobile operators will not suffer much as the decrease will be offset by revenue from new activities. Analysis of the status and specifics of the telecom services market has revealed two issues that merit more detailed consideration: (1) finding the capacity of the telecom services market; (2) forecasting the number of mobile Internet users. An existing method for determining the market capacity is an estimate that takes into account the purchasing activity and the level of demand. For the info-communication market, this is the volume of all expected purchases, namely, the charges for using cellular communication, the Internet and the like for a specific audience for the billing period, for example, one year. We have calculated three types of market capacity using the example of the mobile operator MegaFon: the potential, the available and the actual. The estimation of market capacity was performed taking into account the number of consumers of cellular communication services, the average number of services for data transmission per one subscriber and the average cost of one service for a subscriber. The potential of the market (the difference between the potential and available capacity) allows to determine the growth potential. The given data indicate that the telecommunication market is exhausting itself. In order to be successful in the market, the cellular operators need to expand their business by seeking new directions for development. The Gompertz curve was used to determine the predicted number of mobile Internet users. The graph has an S-shape. The number of subscribers is limited. The number is approaching 137 million people. The forecast was carried out up to 2030. Thus, the stage of saturation takes place at present and the Russian market of infocommunications (in terms of the number of subscribers) has already significantly slowed down its growth. Providing high-speed broadband Internet access, fourth (4G) and then fifth (5G) generation mobile communication and introducing digital services can be considered as a strategic objective.

Telemedicine is a promising direction in the development of medical technologies for the interaction of patients with doctors at a distance. In this paper, we consider the use of telemedicine technologies for the development of smart medical autonomous technology. An example of a smart medical autonomous distributed system for diagnostics is also discussed. To develop this system for medical image analysis we review several processing methods and machine learning algorithms. Some examples of medical system processing results are presented.

The article considers the consequences of the negative influence of signals overlapping from radio emission sources in time. Several examples show that overlapping in time worsens the quality of primary signal processing and, therefore, decreases the stability of radio monitoring systems. A new method of determining the probability of signals overlapping from radio emission sources has been developed. Calculations of the probability of failure of primary processing systems of radio monitoring systems are made.

The authors of this article consider the transfer of data in pheromone networks, which are the application of molecular networks. The authors consider the types of signals that can be used in molecular networks for data transfer (information transfer by moving substances—human and animal pheromones, plant spores and pollen, etc.). The article also discusses the data transmission channel, affecting the channel additive and multiplicative interference. A review of possible interference of natural and man-made nature is made, their possible impact is considered. The article describes the design of a laboratory test bench for conducting an experiment on data transfer by moving a substance, as well as experimental results.

The Internet of Things (IW) is a modern concept for the development of communication networks in the short and long term. The concept implies the integration of devices (“things”), equipped with built-in technologies for interacting with each other or with the external environment, into a single worldwide network. Today, the number of devices connected to the network exceeds the number of all inhabitants of the planet and continues to grow rapidly, which raises the question of assigning each object a unique address to ensure confidentiality and security during data transmission, as well as unique identification of Internet of Things on the global network. The article presents a method for identifying devices and applications of the Internet of Things in heterogeneous communication networks based on the Digital Objects Architecture. It is also proposed to develop methods for installing the DO identifier into devices of the Internet of things with various wireless data transmission modules.

The authors conduct a study of various types of networking in the Industrial Internet of Things, classify the IIoT traffic based on the previously studied types, analyze the IIoT traffic that received during the industrial equipment work. Based on the analysis, a model network for packet generation is proposed to simulate the operation of industrial equipment in communication networks by the authors.

Modern telecommunication networks show steady growth in the digital cable television and IPTV market. In today’s telecommunication networks most of the services are related to transmission of video traffic. For client’s loyalty operators are busy looking for new video delivery optimization methods with the appropriate quality of experience. MEC or Mobile edge computing offers significant advantages for example, enabling operators to bring applications and content closer to the network edge i.e. close to the video content end consumer and other advantages. This is particularly interesting in video delivery, where latency negatively affect video quality. Users can receive video content with minimum delays and operators can realize operational and cost efficiencies while reducing network latency and, ultimately improving the end consumer’s quality of experience. In this paper, a video content application migration method using edge-computing technology is proposed. The proposed method is applied in a managed mode over a Software-Defined Networking (SDN); what improves the efficiency of video traffic delivery. A new concept “Exchange” is introduced for flexible and automated interaction between video delivery chain members, i.e. the network operator, the content provider and the end user.

The recently standardized millimeter wave-based 3GPP New Radio technology is expected to become an enabler for both enhanced Mobile Broadband (eMBB) and ultra-reliable low latency communication (URLLC) services specified to future 5G systems. One of the first steps in mathematical modeling of such systems is the characterization of the session resource request probability mass function (pmf) as a function of the channel conditions, cell size, application demands, user location and system parameters including modulation and coding schemes employed at the air interface. Unfortunately, this pmf cannot be expressed via elementary functions. In this paper, we develop an accurate approximation of the sought pmf. First, we show that Normal distribution provides a fairly accurate approximation to the cumulative distribution function (CDF) of the signal-to-noise ratio for communication systems operating in the millimeter frequency band, further allowing evaluating the resource request pmf via error function. We also investigate the impact of shadow fading on the resource request pmf.

The introduction of Web 2.0 and Web 3.0 has changed not only the available web technologies, but also the ways in which users interact. The growing ubiquity of Internet access and a variety of mobile devices have allowed people to choose the most attractive tools and services. The conditions of the created environment are well suited for conducting group decision making processes: a large number of users participate in the network, each of whom has his own interests, knowledge and experience. Despite the huge technological leap, there are still problems to be solved. First, in social networks, people communicate and express opinions with the help of words, while traditional methods of group decision making operate with exact numbers. Experts are required to provide estimates in terms of qualitative aspects. Secondly, it is not enough to find a joint solution for all experts, it is also necessary to reach an acceptable level of consensus. The purpose of this work is to conduct a numerical analysis of the group decision making process in social networks, using user publications as ratings. The paper also proposes a format for conducting a process of reaching consensus and its analysis, using the advantages and features of social networks.

Next to come 5G New Radio (NR) radio access technology is foreseen to support a massive number of “resource-hungry” connections and provide high-quality services. Multimedia Broadcast/Multicast Service over Single Frequency Network (MBSFN) for NR, expected in forthcoming 3GPP releases, will enable the simultaneous delivery of the same content over the multiple 5G cells synchronized in time. In this paper, we show that Device-to-Device (D2D) communications can improve the MBSFN network coverage, data rate, and latency for the future 5G use cases. More specifically, we propose a new D2D-aided MBSFN area formation algorithm, which foresees that in such an area the content can be delivered through either MBSFN or D2D transmissions. Achieved simulation results testify that our proposed algorithm is able to improve the system Aggregate Data Rate (ADR) and, at the same time, to satisfy the user’s requirements.

Here we present a jitter calculation for correlated traffic. As a model, we consider a general-type queuing system, where the distribution of packet interarrival time and service time are approximated by hyperexponential distributions. We use a method that allows us to consider correlation properties through the parameters of these distributions. The resulting expression for jitter allows to calculate its average value with known or estimated statistical characteristics of random interarrival time, service time and packet waiting time for a general type queuing system serving correlated traffic. We show the calculation of packet jitter for real IPTV traffic both with pronounced correlation properties and without correlation. The dependence of the packet jitter value on the utilization coefficient is also given. We made the comparison of the results of analytical evaluation of packet jitter with the results of simulation conducted in the ns2 system, where a two-dimensional sequence was captured on the real network and consisted of packet generation times and their lengths.

The technology of network slicing allows network resources to be distributed among virtual mobile operators in the context of a general increase in the amount of information transmitted. It is important to guarantee the quality of service requirements for user delays. For effective resource sharing, a mathematical and simulation model of a queuing system with elastic traffic, finite queue, and a finite number of sources has been developed. A numerical analysis of such characteristics as the average time and the average number of requests in the system, the share of resource utilization was performed.

5G technology is designed to resolve issues such as the growth of mobile traffic, the increase in the number of devices connected to the network, reducing delays for the implementation of new services and the lack of a frequency spectrum. The main services in future 5G networks are enhanced Mobile Broadband (eMBB), massive Machine Type Communications (mMTC) and Ultra Reliable Low Latency Communications (URLLC).In this paper, we consider two cases of joint eMBB and URLLC transmissions. In the first case, when all resources are occupied, the blocking of new requests happens, and in the second case, it is possible to reduce the transmission speed of the eMBB application and accept the new URLLC request for service.

This paper proposes new formulation and solution of optimization problems to synthesis bandwidth-efficient signals. Different types of optimization problems such as maximizing free Euclidean distance and minimizing partial correlation coefficients with and without capacity constraint are considered to obtain optimal pulses. Spectral mask is used as additional constraint for optimization problem instead of using bandwidth calculation. Spectral mask templates and other system parameters are taken from DVB-S2 standard. The optimization problems are solved for multicomponent signals which are the kind of partial response signals with finite pulses. BCJR demodulator is used in order to deal with intentional intersymbol interference (ISI). In presence of LDPC and BCH coding, the system with proposed optimal finite pulses provides 10% bandwidth efficiency gain and suffers energy losses of 0.1 dB and 0.25 dB compared to the system with RRC-pulses for QPSK and 8PSK respectively.

Using signals with pulse amplitude modulation (PAM) provides a higher transmission rate in the same frequency bandwidth. However, decreasing frequency bandwidth in order to improve spectral efficiency causes degradation of bit error rate (BER) performance. To minimize energy losses faster than Nyquist (FTN) signaling on the basis of RRC pulses or optimal pulses may be applied. In this work, the possibility of improving BER performance of coherent bit-by-bit detection for optimal FTN signals with increased size of PAM signal constellation is considered. The optimization problem is solved according to the specified size of signal constellation (M). Comparison between RRC pulses and obtained optimal pulses in time and frequency domain is made. It is shown that signals with PAM based on obtained optimal pulses provide an energy gain up to 7 dB regarding signals with RRC pulses for M = 64 at error probability 10−4.

Optimal signals represent the branch of FTN signaling and may be used for spectral efficiency improvement. Such signals may be detected with a simple coherent bit-by-bit algorithm if the transmission rate is equal to the one defined in the optimization problem. In this case, bit-error rate (BER) performance is close to the theoretical one. Extra increase in symbol rate leads to the necessity of application of more complex detection algorithms. In this paper, different detection algorithm including Viterbi algorithm and maximum likelihood sequence estimations are compared. It is shown that for an 11% increase in the symbol rate algorithm of partial enumeration with 2 iterations may be used instead of the Viterbi algorithm because provides almost the same BER performance with less computational complexity.

Simulation modeling of information transmission using spectrally efficient multi-frequency signals with an amplifier and a limiter on transmission was held. The possibility of increasing the average radiation power while limiting the peak-to-average power ratio (PAPR) is shown. However, with a more significant limitation on the PAPR, a greater interference between signals from adjacent subcarriers begins to appear. Thus, it is possible to search for an effective value for PAPR limiting. In this paper, cases of multi-frequency signals are considered with a different value of the frequency separation between subcarriers, and the case of the simultaneous use of a smoothed shape of envelopes is affected.

In this work, a dual-hop relaying system using the differential amplify-and-forward relaying scheme along with post-detection selection combining techniques is proposed. This technique used previously received samples to estimate current fading gain in a branch in order to accomplish a cooperative diversity at cases that exclude the need of having explicit channel estimation. A closed-form expression for the exact end-to-end bit error rate of the communication system, assuming M-ary phase-shift keying constellation over independent non-identical Nakagami-m fading channels, is derived. Different fading parameters were used to validate the correctness of our end-to-end bit error rate tight expression.

The deficiencies of regular cooperative relaying schemes were the main reason behind the development of Incremental Relaying (IR). Fixed relaying is one of the regular cooperative relaying schemes and it relies on using the relay node to help in transmitting the signal of the source towards the destination despite the channel’s condition. However, adaptive relaying methods allocate the channel resources efficiently; thus, such methods have drawn the attention of researchers in recent years. In this study, we analyze a two-hop Decode-and-Forward (DF) IR system’s performance via Nakagami-m fading channels with the existence of the several L distinguishable interferers placed close to the destination which diminishes the overall performance of the system due to the co-channel interference. Tight formula for the Bit Error Rate (BER) is drawn. The assumptions are consolidated by numerical calculations.

The article discusses the problems arising from the modernization of active phased antenna arrays (for example, an increase in the number of transceiver active elements, a decrease in the weight and size of the antenna system, etc.). It has been substantiated that the most rational solution of these problems is the use of fiber-optical communication systems for transmitting heterodyne signals. A new design of the transmit-receive module with a fiber-optic transmission system for an active phased antenna array has been developed. The results of experimental investigations are presented.

The design of an acousto-optic-fiber simplex communication channel based on a two-mode optical fiber is proposed. The model of this channel has been described and the simulation of data transmission over such channel has been executed. The simulation results are presented. As examples the dependencies of bit error rate from a cumulative differential mode delay in the fiber optic link. They showed that, for optimal reception, the accumulated differential mode delay should lie within 1.1–1.5 rad. Measures are proposed to ensure the required value of a differential mode delay at the receiver input.

A broad band fiber optic link with a stand-alone remote external modulator at the transmission terminal and laser source and photo detector at the receiving terminal have been demonstrated. The standard single mode fiber without polarization maintaining was used to deliver an optical radiation to the polarization sensitive lithium niobate external modulator. An original scheme with depolarizing laser sources was used. One component of the linear polarization was used for high frequency modulation and the orthogonal component was converted into electricity and feed the modulator bias control electronic scheme. The using of the balanced detection scheme for the increasing spurious-free dynamic range (SFDR) higher than 110 dB/Hz2/3 was proposed.

This paper presents an experimental study of the interference caused by rotating magnetic fields in interspecies molecular communication. During the experiment, we considered microbial-plant biosystem interaction under the effect of magnetic fields. This study has been one of the first attempts to examine the interference of electromagnetic field to molecular communication. The results of the experiment demonstrate that molecular communication channels can be sensitive to the influence of magnetic fields. Particularly, the experimental results reported in the paper indicate that molecular communication was blocked by magnetic fields.

Features of control systems and various systems for monitoring the parameters of nuclear power plants using fiber - optical communication systems are considered. A system of control and monitoring of the values of various physical parameters for a low-power nuclear power plant with a Brest-OD-300 reactor has been developed. Various fiber-optic sensors are presented that are integrated without additional devices into a single monitoring and control system. The measurement results are presented. The necessity of continuing development and research in this direction has been substantiated.