Review of Simulators for Wireless Mesh Networks, Journal of Telecommunications and Information Technology, 2014, nr 3

The research of computer networks construction of models that reect the current audited environment to carry out practical research is extremely difficult and often involves significant costs. Hence, the popularity of simulation tools that help developers to determine as early as at the stage of the simulation whether a given solution can be deployed in a real network. However, over time many different simulation tools have been developed, each with different characteristics, different uses, different strengths and weaknesses. It is the task of the researcher then to select, before starting the actual research, one of the available simulators in accordance with the needs and adopted criteria of evaluation. In the article the authors present issues related to the simulation tools and the main advantages of simulation as well as their drawbacks. To help researchers select an appropriate simulation environment, the authors present statistical information gathered during a literature survey of a number of research articles from the most popular publishers in which the selected simulators were used in initial system design

Innovative Method of the Evaluation of Multicriterial Multicast Routing Algorithms, Journal of Telecommunications and Information Technology, 2013, nr 1

Theoretical considerations of the multicast Quality of Service (QoS) routing have been a rapidly developing and dynamic research area for years. Several algorithms derived from different approaches have been proposed, while the pool of valid solutions to the problem is steadily growing. When new solutions are compared with their predecessors, as much information as possible about their characteristics and differences is needed. Both the graph theory and the optimization theory provide robust and objective means of comparing not only algorithms, but also the results they produce. However, any possible extension to the comparison methods is vital and can bring interesting new information that would eventually lead to innovative conclusions. This article presents a method, derived from practice and experience, that simulates the drainage of resources accumulated by consecutive communication allocations. The nature of this comparison is an extension to the classical measurement of the success ratio and this creates a context of the continuous measure of a success rather than a simple binary value. In this article such a method with regard to algorithms optimizing multicast problems for more than two criteria is used for the first time and leads to an interesting conclusion about the influence of the number of the criteria on the result

Comparison of Multicast Algorithm Evaluation Results in Low and High Multicast Saturation Environments, Journal of Telecommunications and Information Technology, 2019, nr 3

The multicast quality of service-enabled routing is a computationally challenging task. Despite ongoing research efforts, the associated mathematical problems are still considered to be NP-hard. In certain applications, computational complexity of finding the optimal connection between a set of network devices may be a particularly difficult challenge. For example, connecting a small group of participants of a teleconference is not much more complex than setting up a set of mutual point-to-point connections. On the other hand, satisfying the demand for such services as IPTV, with their receivers constituting the majority of the network, requires applying appropriate optimization methods in order to ensure real system execution. In this paper, algorithms solving this class of problems are considered. The notion of multicast saturation is introduced to measure the amount of multicast participants relative to the entire network, and the efficiency of the analyzed algorithms is evaluated for different saturation degrees

Editors’ Note on the Special Section, Journal of Telecommunications and Information Technology, 2021, nr 2

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Simulations of the MAC Layer in the LoRaWAN Networks, Journal of Telecommunications and Information Technology, 2020, nr 2

The Internet of Things is changing the approach to data transmission, protocol design and network services. The challenge faced by designers of IoT solutions is to determine the scalability of a given technology, with a particular emphasis placed on unlicensed frequency bandwidth (ISM) transmission in highly urbanized areas. Because the design and implementation of a wireless network for the Internet of Things, relying on each of the presented technologies, is expensive and time consuming, it must be preceded by a performance assessment based on computer simulations. The literature contains various approaches to modeling the mechanisms of the MAC layer of LoRa technology and to its implementation in LoRaWAN networks. The article provides an overview of major LoRa MAC network simulators. It presents and comments on the most important research results obtained by the authors of the aforementioned softwar

Traffic Modeling in Industrial Ethernet Networks

This article discusses the traffic types typically used in industrial networks. The authors propose a number of methods of generating traffic that can be used in modeling traffic sources in the networks under consideration. The proposed traffic models have been developed on the basis of the ON/OFF model. The proposed solutions can be applied to model typical traffic types that are used in industrial systems, such as Time-Triggered (TT) traffic, Audio-Video Bridging (AVB) traffic or Best Effort traffic. The article discusses four traffic models with modifications and shows how the proposed models can be used in modeling different traffic types used in industrial networks

Analytical Modelingof the WCDMA Interfacewith Packet Scheduling, Journal of Telecommunications and Information Technology, 2009 nr 3

The article presents the application of a new analytical model of the full-availability group carrying a mixture of different multi-rate traffic classes with compression property for modeling the WCDMA radio interface with packet scheduling. The proposed model can be directly used for modeling of theWCDMA interface in the UMTS network servicing different traffic classes. The described model can be applied for a validation of the efficiency of the WCDMA interface measured by the blocking probability and the average carried traffic for particular traffic classes

Traffic Modeling in Industrial Ethernet Networks

This article discusses the traffic types typically used in industrial networks. The authors propose a number of methods of generating traffic that can be used in modeling traffic sources in the networks under consideration. The proposed traffic models have been developed on the basis of the ON/OFF model. The proposed solutions can be applied to model typical traffic types that are used in industrial systems, such as Time-Triggered (TT) traffic, Audio-Video Bridging (AVB) traffic or Best Effort traffic. The article discusses four traffic models with modifications and shows how the proposed models can be used in modeling different traffic types used in industrial networks

Telecom Operator’s Approach to QoE, Journal of Telecommunications and Information Technology, 2022, nr 2

Telecommunication networks are ever more frequently relying on artificial intelligence and machine learning techniques to detect specific use patterns or potential errors and to take automated decisions when these are encountered. This concept requires that methods be employed to measure the level of quality of a given telecommunication service, i.e. to verify quality of service (QoS) metrics. In a broader context, methods assessing the entire user experience (quality of experience – QoE) are required as well. In this article, various approaches to assessing QoS, QoE and the related metrics are presented, with a view to implement these at an FTTH network operator in Poland. Since this article presents the architecture of the system used to analyze QoE performance based on a number of QoS metrics collected by the operator, we also provide a comprehensive introduction to the QoS and QoE metrics used herein