Joanna Weissenberg

This article presents the development of a real-time system simulator and discusses the results obtained through its application. The simulator is designed in accordance with the fundamental principles of real-time systems, incorporating traffic sources that generate both hard and soft data streams. Hard data streams demand stringent transmission conditions, such as minimal latency beyond what is required for essential operations to ensure accurate data transmission. Conversely, soft data streams allow for variations in transmission parameters. The simulator was developed using the event scheduling approach and implemented in the C++ programming language.

This article proposes an analytical model of a multi-service hierarchical system with multi-service overflow traffic. To model the primary and secondary resources of this system, the state-dependent queue service discipline was used. In order to model the secondary resources with the dedicated queue for overflow traffic, the Hayward’s approach was generalized and applied. To evaluate its accuracy, the results of analytical modeling were compared with the data obtained during the simulation experiments carried out in the study. Both the data presented in the article and the results obtained by the present authors in numerous comparative studies clearly indicate that the proposed model makes it possible to evaluate the values of the blocking probability with the accuracy that provides its reliable practical application at the stage of network dimensioning. The overflow mechanism has particular significance in networks with limited resources, such as mobile networks.

This paper introduces a new analytical model of a multi-service system to which a heterogeneous mixture of stream, elastic, and adaptive traffic is offered, corresponding to data streams transmitted in real-world networks. The heterogeneity results from the coexistence of compressed and non-compressed traffic classes, where the compressed traffic is subject to a finite compression mechanism and includes both elastic and adaptive traffic. The model accounts for access constraints on resources for stream traffic, a strategy frequently used in modern ICT networks to manage the impact of high-rate data streams on overall system performance. The proposed model is developed based on an analysis of the service process within the system using multi-dimensional Markov processes. To assess the accuracy of the analytical model, a digital simulation is conducted. A comparative analysis of the results obtained from the analytical model and the simulation experiments confirms the high accuracy and robustness of the proposed approach, making it suitable for the design and optimization of modern ICT networks, including 5G systems.

This paper presents an analytical model for a railway mobile communications system. In line with recent trends, the system’s operation relies on 5G network resources (slices). It efficiently manages critical data streams (flows) that meet the stringent requirements of real-time systems (systems that handle hard and soft real-time services). Additionally, the proposed solution accommodates data with less stringent QoS parameters compared to real-time streams. The analytical model serves as an approximation of the process occurring in the system for servicing flows and has been developed based on the analysis of a Markov chain, where the states correspond to the states of the examined system. Due to the approximate nature of the analytical model, the results derived from it were compared with those obtained from the simulation experiment.

Disease outbreaks and pandemics show us how important it is to limit the spread of diseases. One common indicator of many ailments is body temperature. It’s a measurement that can be taken quickly, also using contactless methods. However, it is necessary to ensure the methodological correctness, repeatability and reliability of such measurement. In this manuscript, we introduce a non-intrusive approach for individual body temperature assessment that adheres to the stipulated criteria outlined by ISO/IEC 80601-2-59 standard. The measurements are performed at specific regions of interest (ROIs) of a human face, at the inner canthi of both eyes, which show high robustness to the environment temperature change. The method utilises the fusion of RGB-D (red, green, blue and depth) and thermal cameras. The system detects the ROIs on the RGB image employing deep learning methods and transfers them to the thermal image, from which the temperature can be read. The system was tested on our validation dataset consisting of 210 individuals, achieving ROI’s position identification mean error below 3 mm and temperature measurement error below 0.5°C, which is in line with the ISO norm requirements.

This article proposes a new analytical model of a queuing system to which a mixture of multi-service traffic is offered. The system under consideration has the advantage of servicing calls, in a shared server, of which only part will be placed in a queue when the server has no free resources (while the remaining part of the calls will be lost). In addition, this model also introduces the possibility for a compression mechanism to be applied for a selected number of data flows. The possibility of simultaneous analysis of the calls that can be placed in the queue as well as of those in which queuing is not implemented, while a certain number of them can be compressed, provides unquestionable advantage to the proposed model. The proposed model can be successfully applied to analyse and model 5G systems.

The article presents the findings of a study that evaluates the feasibility of using an analytical model for a multi-service queuing system with a SDFIFO queuing service discipline and finite compression mechanism to approximate queuing systems with different queuing service disciplines (e.g., FIFO, cFIFO) while also incorporating finite compression. The evaluation involves comparing results obtained from an analytical model with those of simulation studies. The study considers the blocking probability and average queue length as factors. Additionally, two types of compressed traffic were analysed: elastic and adaptive. These are characteristic of modern telecommunications networks, particularly in multimedia applications. This paper is an extended version of our paper published in 4th CoBCom 2022.

This paper presents an analytical model of a multiservice queueing system that services elastic and adaptive BPP traffic. The model presented in the paper was developed as an extension of earlier works published by the authors. The model is based on several concepts specific to modelling multi-service systems. In order to derive the model, the idea of equivalent bandwidth and the discretisation process were used first. Subsequently, the MIM-BPP method was generalised in relation to a system with traffic that undergoes the compression mechanism. Since the proposed model is an approximate one, the results of the calculation are compared with the simulation results. The comparison of the results confirms the accuracy of the proposed model.