Bandwidth Of Communication Channel Research Articles

Migration Route Selection for a Microservice in a Fog Computing Network

Purpose. The new generation of communication networks has provided the basis for the realization of new classes of services, one of which are URLLC services. These services include concepts such as Tactile Internet. The transmission medium for URLLC requires high bandwidth and reliability of communication channels as well as ultra-low latency in the network. To cover these requirements, various technologies, such as fog computing and microservice architecture, are introduced into the architecture of networks. The latter is more often recommended to be used together with support for microservice migration between devices. A related goal is to determine the efficient route to the destination server. Methods. Conducting research on a model network with the collection of real load statistics from the network nodes and their analysis to determine the most efficient migration route for microservice according to the proposed algorithm based on these data. Novelty. The novelty of the presented method consists in adapting the classical algorithm of route selection in a graph to solve the actual problem of microservice migration route selection. Results. The parameters that need to be considered for efficient routing during microservice migration and the level of network architecture that should control the migration were defined. The results have shown that the proposed method is preferred over the AODV protocol. Practical relevance. It is quantitatively shown that using the proposed method the CPU resources consumption on the network nodes during microservice migration can be reduced total by 77 %, the RAM resources usage by 14 %, the percentage of lost packets on the used communication channels can be reduced total by 7 %, which would provide higher network reliability and increase its performance.

A method for extracting the semantic features of speech signal recognition based on empirical wavelet transform

The subject of this study is methods for improving the efficiency of semantic coding of speech signals. The purpose of this study is to develop a method for improving the efficiency of semantic coding of speech signals. Coding efficiency refers to the reduction of the information transmission rate with a given probability of error-free recognition of semantic features of speech signals, which will significantly reduce the required source bandwidth, thereby increasing the communication channel bandwidth. To achieve this goal, it is necessary to solve the following scientific tasks: (1) to investigate a known method for improving the efficiency of semantic coding of speech signals based on mel-frequency cepstral coefficients; (2) to substantiate the effectiveness of using the adaptive empirical wavelet transform in the tasks of multiple-scale analysis and semantic coding of speech signals; (3) to develop a method of semantic coding of speech signals based on adaptive empirical wavelet transform with further application of Hilbert spectral analysis and optimal thresholding; and (4) to perform an objective quantitative assessment of the increase in the efficiency of the developed method of semantic coding of speech signals in contrast to the existing method. The following scientific results were obtained during the study: a method of semantic coding of speech signals based on empirical wavelet transform is developed for the first time, which differs from existing methods by constructing a set of adaptive bandpass Meyer wavelet filters with further application of Hilbert spectral analysis to find the instantaneous amplitudes and frequencies of the functions of internal empirical modes, which will allow the identification of semantic features of speech signals and increase the efficiency of their coding; for the first time, it is proposed to use the method of adaptive empirical wavelet transform in the tasks of multiple-scale analysis and semantic coding of speech signals, which will increase the efficiency of spectral analysis by decomposing the high-frequency speech oscillation into its low-frequency components, namely internal empirical modes; the method of semantic coding of speech signals based on mel-frequency cepstral coefficients was further developed, but using the basic principles of adaptive spectral analysis with the help of empirical wavelet transform, which increases the efficiency of this method. Conclusions: We developed a method for semantic coding of speech signals based on empirical wavelet transform, which reduces the encoding rate from 320 to 192 bps and the required bandwidth from 40 to 24 Hz with a probability of error-free recognition of approximately 0.96 (96%) and a signal-to-noise ratio of 48 dB, according to which its efficiency is increased by 1.6 times as compared to the existing method. We developed an algorithm for semantic coding of speech signals based on empirical wavelet transform and its software implementation in the MATLAB R2022b programing language.

Output Feedback Control of Sine-Gordon Chain over the Limited Capacity Digital Communication Channel

With the digitalization of mechatronic systems in the conditions of a shortage of available bandwidth of digital communication channels, the problem of ensuring the transfer of information between various components of the system can arise. This problem can be especially challenging in the observation and control of spatially distributed objects due to the complexity of their dynamics, wide frequency band, and other factors. In such cases, a useful approach is to employ smart sensors, in which the measurement results are encoded for transmission over a digital communication channel. Specifically, the article is focused on the transmission of measurement data for the control of energy for a spatially-distributed sine-Gordon chain. The procedures for binary coding of measurements by first- and full-order coder-decoder pairs are proposed and numerically investigated, for each of which the use of stationary and adaptive coding procedures is studied. The procedures for estimating the state of the circuit when measuring outputs are studied, and for each of them, the accuracy of not only estimating the state but also controlling the system by output with the help of an observer is considered. The results of comparative modeling are presented, demonstrating the dependence of the accuracy of estimation and control on the data transfer rate.

Model of Optimal Placement of Cloudlets in a Wireless Metropolitan Area Network

Cloud computing has recently emerged as a new paradigm for processing and storing large amounts of data. The rapid increase in the number of mobile phones and IoT devices benefitingfrom cloud computing services reduces the Internet bandwidth, resulting in delays in delivering data processed on remote cloud servers to the user. Mobile devices use edge computing systems (cloudlet, fog computing, etc.) to overcome resource shortages, power consumption and delays in communication channels. Edge computing systems place processing devices (cloudlets) close to users. The closer the cloudlets to mobile devices, the lower the processing time and energy consumption of the mobile device, and the higher the bandwidth of communication channels. Thus, cloudlet-based mobile computing clouds are widely used to reduce the latency in the Internet communication channels and energy consumption on mobile devices. This article identifies the most popular places for cloud servers in metropolitan mobile networks and discusses the optimal placement of a limited number of cloudlets in those places.

Bipartite Tracking Consensus for High-Order Heterogeneous Uncertain Nonlinear Multi-Agent Systems With Unknown Leader Dynamics via Adaptive Fully-Distributed PID Control

This article tackles the problem of bipartite tracking consensus for high-order heterogeneous nonlinear and uncertain Multi-Agent Systems (MASs) interacting over directed signed graphs, where the agent nonlinear dynamics, including the leader ones, are general and unknown. A novel fully-distributed adaptive PID-like protocol, that does not require any prior knowledge about the global information of the network structure and/or any distributed observer for leader dynamics estimation, is proposed to solve the problem. Based on the Lyapunov theory, we derive adaptive mechanisms able to guarantee the robust asymptotic convergence of the overall networked system and the boundedness of the time-varying control signals. To achieve these control objectives, the computation of the adaptive control actions leverages only a limited amount of time-varying information, thus preserving the communication channel bandwidth and reducing the computational burden required at the single agent level. A numerical analysis supports the theoretical derivation.

Experimental studies of communication channel bandwidth of millimeter wave range indoors

There is a rapid development of technologies worldwide that have access to the Internet, independently exchange data, and upload collected information to cloud storage. Every year, the amount of data transmitted from things and people on the Internet is approximately two zettabytes. The volume of data on the Internet is constantly growing. According to the Internet Live Stats service, more than 50,000 search queries are made on Google every second, 120,000 videos are viewed on YouTube, and almost 2.5 million e-mails are sent. Therefore, it is expedient to implement the fifth generation of communication, which will work in the millimeter range. Promising technologies for building 5G and its implementation include small base stations, which are analogs of conventional mobile network base stations. Within settlements, small base stations should be located short distances from each other (approximately 250 meters). From such parameters, it can be concluded that it will be necessary to use thousands of such stations to cover even a small city, forming a single network that will transmit data to 5G users. Among the advantages, it can be noted that due to the small size of the antennas, they can be placed on any elements of structures and buildings (for example, on the walls of buildings, pillars, etc.) without additional obstacles. The paper presents and investigates the bandwidth of the millimeter wave range indoor communication channel. The structure of the modem and the format of the control command, the dependence of the transmission speed C on the length of the radio line of the IEEE 802.11ad 60 GHz communication system in point-to-point mode (Indoor LOS) and (Indoor NLOS) are presented. In work, there are theoretical assessments of the achievable data transfer rates based on the bandwidth of the Shannon communication channel and practically possible data transfer rates for various segments of the information transfer network for the IEEE 802.11ad standard equipment using different modulation and coding schemes (MCS).

Quantized Distributed Online Projection-Free Convex Optimization

This paper considers online distributed convex constrained optimization over a time-varying multi-agent network. Agents in this network cooperate to minimize the global objective function through information exchange with their neighbors and local computation. Since the capacity or bandwidth of communication channels often is limited, a random quantizer is introduced to reduce the transmission bits. Through incorporating this quantizer, we develop a quantized distributed online projection-free optimization algorithm, which can achieve the saving of communication resources and computational costs. For different parameter settings of the quantizer, we establish the corresponding dynamic regret upper bounds of the proposed algorithm and reveal the trade-off between the convergence performance and the quantization effect. Finally, the theoretical results are illustrated by the simulation of distributed online linear regression problem.

Dynamic Characteristics Preserving Data Compressing Algorithm for Transactive Energy Management Frameworks

Several players are enabled in smart grids and involved in decision-making process. These players are fully interconnected in the transactive energy (TE) framework to operate the system optimally. By implementing the TE, the final decision are adopted after various consensus between participants. Hence, huge number of data and information are communicated in this framework which leads to complex communication algorithms and wide-bandwidth channels. Besides, the prosumers dataset in the TE framework are with low level of sparsity which is due to their independent interactions with peers and the grid. This article proves the low sparsity in the prosumers dataset and shows the shortcomings of the existing methods. A dynamic intelligent algorithm is proposed in this article to characterize the prosumers data based on the mutual information (MI) theorem. In addition, two data compression algorithms have been proposed in this article to reduce the bandwidth and space for communicating and storing purposes, respectively. The proposed algorithms for data modeling and compression provide compatible superlative performance with minimum information loss. This article saves more communication channel bandwidth by comparing the conventional methods. Fast and robust adaptation of the proposed algorithm facilitates the practical implementation of energy management in the TE framework when wide data transmission is needed. The performance of the proposed algorithms has been evaluated using simulated prosumers dataset and real-world residential and industrial consumer data.

A Comprehensive Review on Wired and Wireless Communication Technologies and Challenges in Smart Residential Buildings

Background: The smart grid communication network is constructed with three tiers namely, Home Area Networks (HANs), Neighborhood Area Networks (NANs) and Wide Area Networks (WANs). These networks function with various communication protocols like table protocol, on-demand protocol, Wi-Fi, Zigbee, Z-Wave, Wi-MAX, GSM, LTE, Cognitive Radio Networks. The network interconnection is heterogonous and all appliances have to communicate through the IP gateways. A large amount of data is collected from various sensors placed in different locations. The analytics on large data- “big data” is essential because these data were used to organize and plan an efficient control and management of the smart home including secured data exchange in different sectors. Objective: This paper investigates broadly on data rate, channel bandwidth, power consumption, and a coverage range of both wired and wireless communication technologies used in residential buildings. Besides, a literature survey on optimization algorithms with various constraints to manage home appliances through scheduling is included. The paper also discusses the communication standards along with security and privacy requirements for smart metering networks. Conclusion: Discussion on IEEE standards for both wired and wireless communication protocols. Gives direction to identify the suitable communication technique through mathematical model for computing the communication channel bandwidth. Comparison of various optimization algorithms with multiple constraints in HEMS to achieve the minimum electricity cost and user comfort (with and without Renewable Energy Sources). From the investigation on both wired and wireless networks, the wireless communication networks (Zig-Bee & Wi-Fi) are mostly preferred to use in HAN because of more reliability and low cost. Zigbee is the most appropriate technology used for data transmission between the individual appliances and smart meters. Wi-Fi is a suitable technology for controlling and monitoring appliances because of its high data rate.

Задача управления сенсорной сетью на основе рандомизированного и многоагентного подходов и ее приложения

Tracking multiple targets is a classic signal processing problem that occurs in many applications such as air, maritime and traffic control. Autonomous sensor networks serve as desirable platforms for multipurpose tracking due to their redundancy and reconfigurability. However, the network implementation makes it impossible to use the classical centralized approaches to filtering, since each sensor has limited computing power and limited access to the measurements of other sensors. In addition to topological limitations (each sensor can only communicate with several neighboring network nodes), communication between sensors can be limited, for example, due to limited bandwidth of communication channels, delay and data distortion. This article proposes a new algorithm for distributed tracking of multiple targets in a sensor network, which is a combination of the SPSA algorithm and the local voting protocol. The algorithm is consolidated under conditions of unknown but limited noise, the algorithm step size is optimized, and simulation is carried out to confirm the algorithm’s performance. Possible applications for the algorithm are also described.

Transient Wavelet Energy-Based Protection Scheme for Inverter-Dominated Microgrid

When faults occur in the microgrids, high frequency transients will be superimposed on the system currents and voltages. The magnitude of those transients will attenuate as it encounters the discontinuity points in the network such as busbars, or any other impedance discontinuity points. This phenomenon can also be quantified by wavelet energy, which provides a useful tool to detect faults and locate the faulted feeder in the microgrid. In this paper, a novel protection scheme based on the transient wavelet energy of the superimposed current extracted by the Maximal Overlap Discrete Wavelet Transform (MODWT) algorithm is developed to detect faults and locate the faulted feeder in microgrids. Compared with existing protection schemes, the proposed protection scheme has the advantage of being largely immune to the changes in system fault level, fault types and positions, microgrid operating status and the control strategies deployed on the inverters, while presenting much lower requirement on the sampling frequency (10 kHz) compared with travelling wave-based methods. Unlike the conventional differential protection, the proposed scheme does not require synchronized measurement or high bandwidth communication channels, and thus, it can be considered as an economical and promising solution for microgrids.

Clustering Method of Mobile Cloud Computing According to Technical Characteristics of Cloudlets

The rapid increase in the number of mobile phones and IoT devices connected to the network reduces the bandwidth of the Internet communication channel, and as a result, delays occur in the delivery of data processed in remote clouds. Edge computing systems (cloudlet, fog computing, etc.) are used to eliminate resource shortages, energy consumption, and communication channel delays in mobile devices. Edge computing systems place processing devices (computers) close to users. Cloudlet-based mobile cloud computing is widely used to reduce delays in communication channels and energy consumption in mobile devices. Selection of the most suitable cloudlet allowing users to run applications fast in cloud is still a considerable problem. This paper proposes a strategy for the selection of high-performance cloudlets providing fast solutions, considering the complexity of application (file type). It offers a method for cloudlet selection out of large number of cloudlets with different technical capabilities providing faster processing of user application. The timing of user applications in cloudlets with different technical capabilities (operating frequency, number of cores, volume of RAM, etc.) also varies. The proposed method provides faster solution for the user application. User applications are grouped by type of application, and a set of cloudlets are clustered by the number of groups. Clustering is performed first by the parameters corresponding to the operating frequency of the cloudlets, then by the number of cores and the volume of RAM. The proposed method reduces energy consumption of mobile devices by providing faster processing of applications. Thus, the proposed strategy provides an energy consumption reduction on mobile devices, faster processing of results and decrease of network delays.

Data switching method among heterogeneous power information system databases based on knowledge graph

AbstractIn order to solve the problems of long data switching time, low information utilization rate, and low switching accuracy in traditional data switching methods, a data switching method between heterogeneous power information system databases based on knowledge graphs is proposed. Based on the knowledge graph technology and its ternary structure, the data of the heterogeneous power information system is processed, and the N‐Gram model is used to realize the knowledge extraction, and the data error correction is established through the model. Through ODBC technology to complete the link between heterogeneous power information system databases, and then select the data access interface and determine the data extraction task, and finally realize the data exchange between the heterogeneous power information system databases. Experimental results show that the average communication channel bandwidth during the data switching process is 1.8 Gb/s, the highest value of data switching accuracy reaches 82%, and the information utilization rate after data switching is relatively high, indicating that the method has certain effectiveness.

Аналитический обзор нововведений стандарта IEEE 802.11ax

Nowadays, due to the rapid development of small-scale wireless networks, the increase in the amount of the traffic consumption (due to the pandemic and the transfer of employees to remote work), the increase in the number of wireless devices and the requirements for the bandwidth of communication channels and different delays arising in them, characteristics of the 802.11ac standard the bandwidth described in this standard were no longer enough. To eliminate these shortcomings, the IEEE 802.11ax standard was introduced in 2019, and finally approved on February 1, 2021. This standard is commercially known as Wi-Fi 6. In the 802.11ax standard, developers focused on energy efficiency, capacity and bandwidth of the communication channel. Improving these parameters resulted in a quadruple increase in the average throughput per user and improved customer experience. These improvements are relevant for both external and internal subscribers. The article presented new technologies used in the IEEE 802.11ax (Wi-Fi 6) standard, such as MU-MIMO, OFDMA, Color Code BSS and Beamforming. MU-MIMO allows providers to simultaneously transmit different data to multiple subscriber stations. OFDMA technology allows providers to increase the bandwidth of the communication channel. The Color Code BSS technology allows us to identify the network as a “friend” or a “foe” when exchanging data between the router and other devices within the 802.11ax standard Wi-Fi network.

Long-range underwater acoustic communication of M-eyry spread spectrum with cyclic prefix

The Spread Spectrum is an effective transmission method for complex channels in underwater acoustic (UWA) communication because of the high correlation of pseudo-random noise (PN) sequence. In particular, the spread spectrum method is effective in an environment with a low signal-to-noise ratio. The bandwidth of UWA communication channel is limited due to the fact that sound wave attenuation in water is positively associated with frequency. The limited bandwidth directly leads to the low data rate of conventional direct-sequence spread spectrum UWA communication. M-ary spread spectrum (MSS) schemes using multiple orthogonal PN sequences were proposed as a solution to this problem. However, even in the MSS method, the performance may be limited by the delay spread characteristics in the multipath propagation channels. We propose a more robust communication method in the UWA channel by including Cyclic Prefix (CP) to achieve a more robust performance in the multipath channel. In the proposed method, a CP is inserted for every symbol. In the 160 km long-range UWA communication experiment conducted in the East Sea, the proposed method showed more reliable results than the conventional MSS method. [Work supported by the Agency for Defense Development, South Korea, Grant No. UD200010DD.]

Autonomous Cave Surveying With an Aerial Robot

This paper presents a method for cave surveying in total darkness using an autonomous aerial vehicle equipped with a depth camera for mapping, downward-facing camera for state estimation, and forward and downward lights. Traditional methods of cave surveying are labor-intensive and dangerous due to the risk of hypothermia when collecting data over extended periods of time in cold and damp environments, the risk of injury when operating in darkness in rocky or muddy environments, and the potential structural instability of the subterranean environment. Although these dangers can be mitigated by deploying robots to map dangerous passages and voids, real-time feedback is often needed to operate robots safely and efficiently. Few state-of-the-art, high-resolution perceptual modeling techniques attempt to reduce their high bandwidth requirements to work well with low bandwidth communication channels. To bridge this gap in the state of the art, this work compactly represents sensor observations as Gaussian mixture models and maintains a local occupancy grid map for a motion planner that greedily maximizes an information-theoretic objective function. The approach accommodates both limited field of view depth cameras and larger field of view LiDAR sensors and is extensively evaluated in long duration simulations on an embedded PC. An aerial system is leveraged to demonstrate the repeatability of the approach in a flight arena as well as the effects of communication dropouts. Finally, the system is deployed in Laurel Caverns, a commercially owned and operated cave in southwestern Pennsylvania, USA, and a wild cave in West Virginia, USA.

Research of methods and means of signal modulation with high interference resistance in modern mobile networks

Systems of multiposition signals are investigated, on the basis of which it is possible to reach the transmission speeds close to the bandwidth of communication channels. In communications systems, where the most stringent requirements for noise immunity are the most effective, it is most efficient to use multi-position signals with phase-difference modulation, for which the equivalent energy is maximal. The optimal incoherent reception has the status of optimal for signal variants with an unknown and uniformly distributed initial phase. Optimal incoherent reception is understood as a non-coherent processing method that ensures the minimum probability of error when receiving signal elements in a channel with Gaussian white noise with a random and uniformly distributed initial phase of the received element (about which nothing else is known). All other non-informative parameters of the signal, except for the initial phase, primarily - the frequency and processing interval, with optimal non-coherent reception, must be known precisely. As for the signal amplitude, when using signals with equal energy, it may be unknown. With regard to FM signals, the optimal incoherent method of reception can be used only to determine the phase of the transmitted difference (and not the absolute phase), which is fundamentally unknown with this processing method. The main method of synthesis of algorithms for optimal incoherent reception of signals from FRM-1 is considered, which considers all possible situations when processing signals on two parcels. An algorithm for optimal incoherent reception of signals from FDM-1 is developed, suitable for implementation with any set of information phase differences. The algorithm of optimal incoherent reception of signals from FDM-2 is developed. It is concluded that the optimal incoherent reception of signals from the FDM allows, by increasing the processing interval, to approach the potential impedance of the given signal system without evaluating the initial phase.

Application of region-based video surveillance in smart cities using deep learning

Smart video surveillance helps to build more robust smart city environment. The varied angle cameras act as smart sensors and collect visual data from smart city environment and transmit it for further visual analysis. The transmitted visual data is required to be in high quality for efficient analysis which is a challenging task while transmitting videos on low capacity bandwidth communication channels. In latest smart surveillance cameras, high quality of video transmission is maintained through various video encoding techniques such as high efficiency video coding. However, these video coding techniques still provide limited capabilities and the demand of high-quality based encoding for salient regions such as pedestrians, vehicles, cyclist/motorcyclist and road in video surveillance systems is still not met. This work is a contribution towards building an efficient salient region-based surveillance framework for smart cities. The proposed framework integrates a deep learning-based video surveillance technique that extracts salient regions from a video frame without information loss, and then encodes it in reduced size. We have applied this approach in diverse case studies environments of smart city to test the applicability of the framework. The successful result in terms of bitrate 56.92%, peak signal to noise ratio 5.35 bd and SR based segmentation accuracy of 92% and 96% for two different benchmark datasets is the outcome of proposed work. Consequently, the generation of less computational region-based video data makes it adaptable to improve surveillance solution in Smart Cities.

Protection of converter dominated MV microgrid using changes in current's phase angle

Converter interfaced distributed generations in a microgrid feed the modulated current of limited magnitude during fault conditions. The protection design and its operation are thus challenging due to limited fault current which is further reduced by Petersen coil grounding in medium-voltage (MV) level. This paper aims to address this challenge by developing a current-only directional relay algorithm for the protection of converter dominated MV microgrid with Petersen coil grounding. The relay's operating principle is based on the sign of the change in phase angle of the fault current with respect to the prefault which indicates the direction of fault. The negative and positive changes in current's phase angle determine the fault in forward and reverse direction, respectively. The tripping decision is derived by comparing the binary output of the relay at both ends of the line segment under protection. This requires a simple, flexible and low bandwidth communication channel. Both theoretical analyses and simulation studies have been performed on a typical distribution grid intended to be operated as microgrid. The proposed protection method is suitable for microgrid having the converters with and without reactive power support. Various operating conditions are evaluated, including bidirectional power flow, high resistance fault, different fault types, loading conditions and signals with noise.

Design of a 10 GHz optical wireless communication link using low power C-band laser diode

This article deals with the proposed design of a 10 GHz optical wireless communication (OWC) link using 1550 nm Laser source for long range communication channel. Optical communication is the backbone of next generation gigabit class communication system and optical fiber communication plays an important role to fulfill the requirement of gigabit communication. But OWC is very useful where optical fibers cannot be laid off. A 10 GHz communication channel bandwidth has been designed in this article using very low power (2 mW) 1550 nm laser diode. A long range communication channel of 3 km has been considered with maximum bit-error-rate (BER) of 10−9. This system has been designed to withstand high atmospheric attenuation up to 11.67 dB/km, without affecting the BER and link range. An auto alignment method and automatic laser power control method have also been described with all necessary design parameters of the system.