The LP WAN networks use gateways or base stations to communicate with devices distributed on large distances, up to tens of kilometres. The selection of optimal gateway locations in wireless networks should allow providing the complete coverage for a given set of nodes, taking into account the limitations, such as the number of nodes served per access point or required redundancy. In this paper, we describe the problem of selecting the base stations in a network using the concept of k-dominating set. In our model, we include information about the required redundancy and spectral efficiency. We consider the additional requirements on the resulting connections and provide the greedy algorithm for solving the problem. The algorithm is evaluated in randomly generated network topologies and using the coordinates of sample real smart metering networks.
01790nas a2200169 4500000000100000000000100001008004100002260001200043100002100055700002200076700001900098700002200117245011500139856004500254490000700299520131400306 2021 d c01/2021 1 aMichał Gorawski 1 aKrzysztof Grochla 1 aRafał Marjasz 1 aArtur Frankiewicz 00 aEnergy Minimization Algorithm for Estimation of Clock Skew and Reception Window Selection in Wireless Networks uhttps://www.mdpi.com/1424-8220/21/5/1768 0 v21 3 aThe synchronization of time between devices is one of the more important and challenging problems in wireless networks. We discuss the problem of maximization of the probability of receiving a message from a device using a limited listening time window to minimize energy utilization. We propose a solution to two important problems in wireless networks of battery-powered devices: a method of establishing a connection with a device that has been disconnected from the system for a long time and developed unknown skew and also two approaches to follow-up clock synchronization using the confidence interval method. We start with the analysis of measurements of clock skew. The algorithms are evaluated using extensive simulations and we discuss the selection of parameters balancing between minimizing the energy utilization and maximizing the probability of reception of the message. We show that the selection of a time window of growing size requires less energy to receive a packet than using the same size of time window repeated multiple times. The shifting of reception windows can further decrease the energy cost if lower packet reception probability is acceptable. We also propose and evaluate an algorithm scaling the reception window size to the interval between the packet transmission
00424nas a2200145 4500000000100000000000100001008004100002260002900043100001700072700002200089700002200111700002700133245006900160856004900229 2022 d bIEEE aDubrovnik, Croatia 1 aAnna Strzoda 1 aKrzysztof Grochla 1 aArtur Frankiewicz 1 aZbigniew Łaskarzewski 00 aMeasurements and Analysis of Large Scale LoRa Network Efficiency uhttps://ieeexplore.ieee.org/document/9824317 01207nas a2200157 4500000000100000000000100001008004100002260003200043100002100075700001900096700002200115700002200137245011700159856005000276520072300326 2024 d c08/2024 bIEEE aThessaloniki 1 aMichał Gorawski 1 aRafał Marjasz 1 aKrzysztof Grochla 1 aArtur Frankiewicz 00 aComparative Analysis of Energy Consumption in Simulated LoRa Water Meter Reconfiguration vs. Real-world Readings uhttps://ieeexplore.ieee.org/document/10619861 3 aDetecting water leaks in distribution networks is crucial for conserving resources and preventing infrastructure damage. However, one of the most basic and significant challenges before employing any leak detection method is collecting data from the water distribution network. The sensors used for data collection are usually battery-powered; thus, the energy consumption of these devices is an essential factor. In this paper, we analyze the battery consumption of real devices placed in an operational water distribution network, and based on the obtained data, we perform a series of complex simulations to validate the preliminary assumptions we plan to use in further research of leak detection methods.
00382nas a2200109 4500000000100000000000100001008004100002100002200043700002200065245007900087856010600166 2024 d 1 aArtur Frankiewicz 1 aKrzysztof Grochla 00 aOcena wydajności mechanizmu retransmisji TS011_1. 0.0 w sieciach LoRa WAN uhttps://yadda.icm.edu.pl/baztech/element/bwmeta1.element.baztech-ca38f38f-5189-4f56-b397-df8beb305838 01709nas a2200145 4500000000100000000000100001008004100002260004700043100002200090700002200112245009600134856006700230520124400297020002201541 2026 d c01/2026 bSpringer Nature Switzerland aCham 1 aArtur Frankiewicz 1 aKrzysztof Grochla 00 aUsing Time Series Analysis to Generate Synthetic Traffic Data for LoRa Network Simulation uhttps://link.springer.com/chapter/10.1007/978-3-032-04197-5_16 3 aModelling radio signal attenuation in Low Power Wide Area Networks (LPWANs) is a complex challenge due to the numerous factors influencing signal propagation and attenuation. Recent advancements in artificial intelligence have enabled the use of neural network-based time series analysis to develop radio attenuation models suitable for radio simulators. In this paper, we evaluate the feasibility of such AI-driven models for discrete event simulations. To train and validate these models, we utilize data collected from a large-scale LoRaWAN network that has been operational for over six years. The trained model is then applied to generate synthetic data for radio network simulations. We compare the AI-generated data with conventional distribution-based generators, assessing their effectiveness in modelling real-world events and analysing the statistical distribution of the generated data. Finally, we discuss the benefits and limitations of using AI-based models for simulation purposes. While traditional generators typically produce data distributions that closely mirror real data, AI algorithms are more effective at capturing specific patterns found in actual datasets what is challenging with conventional methods.
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