Analysis of Processes Affecting Sensor Network Performance

Introduction. This article analyzes the processes that affect the performance of wireless sensor networks (WSNs) in the context of self-similar traffic. It explores the features of various packet flow distribution strategies (continuous probing, request-driven, event-driven, and hybrid) and their compliance with quality of service (QoS) requirements. Wireless sensor networks (WSNs) are essential for smart homes, wearable devices, and Industry 5.0 and smart city projects. They automate processes using remotely controlled actuators and microelectromechanical systems (MEMS)-based monitoring systems, and collect big data. A key segment of the BSS is the Internet of Things (IoT), which requires improved network performance and reliability due to the increasing number of connections and traffic. Existing solutions often struggle to cope, highlighting the need for IT infrastructure adaptation. The study is relevant due to the contradictions between the growing needs of IoT and the limited capabilities of networks.

Materials and methods. The goal of this work is to analyze the processing of self-similar traffic in BSS and develop recommendations for optimizing the architecture and parameters of networks. The main objectives include modeling self-similar flows and evaluating performance under high data transfer rates. Materials and methods. Using the method of slowly varying amplitudes, the system of mass, energy, and momentum conservation equations for both phases is reduced to a single nonlinear wave equation.

Results and discussion. The results will help optimize the IT infrastructure for the efficient operation of BSS when the number of devices increases. Attention is paid to the proven self-similar nature of BSS traffic, which significantly affects network performance. Technological solutions for IoT, including LPWAN technologies (LoRaWAN, NB-IoT), are considered, and the problems of ensuring QoS during ultra-dense deployment of sensor devices are identified.

Conclusion. The paper analyzes the factors affecting the performance of wireless sensor networks (WSNs) when serving self-similar traffic. The main conclusions are: WSNs require traffic distribution strategies that comply with QoS standards. Self-similar traffic complicates QoS provisioning due to the inefficiency of classical models, and fractal models are needed. Network gateways become a bottleneck, and traffic management mechanisms such as AQM and intelligent classification are required. LPWAN technologies (e.g., LoRaWAN) require protocol adaptation for ultra-dense deployments. Heterogeneous BSSs require traffic prioritization, AQM, smoothing, and forecasting. The agriculture sector requires intelligent traffic classification to manage latency, bandwidth, and loss. To improve BSS performance, comprehensive optimization is needed, including adaptive QoS mechanisms and advanced technologies.

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