ОПТИМИЗАЦИЯ ВРЕМЕННЫХ ХАРАКТЕРИСТИК БЕСПРОВОДНОЙ СЕНСОРНОЙ СЕТИ АГРОПРОМЫШЛЕННОГО МОНИТОРИНГА МЕТОДОМ АДАПТИВНОЙ ФРАГМЕНТАЦИИ ПАКЕТОВ

Владимир Валерьевич Самойленко

doi:10.17308/sait/1995-5499/2026/1/52-66

Authors

Vladimir V. Samoylenko Stavropol State Agrarian University

DOI:

https://doi.org/10.17308/sait/1995-5499/2026/1/52-66

Keywords:

wireless sensor network (WSN), precision agriculture, wireless communication, bit error rate (BER), automatic repeat request (ARQ), rician K-factor, packet fragmentation, end-toend delay (E2E delay)

Abstract

The relevance of this study is driven by the increasing adoption of wireless sensor networks (WSNs) as a technological platform for precision agriculture and smart horticulture. Efficient management of drip irrigation and microclimate based on WSN data can reduce water consumption by 30–40 % and fertilizer use by 15–25 %. A factor hindering the widespread implementation of these technologies in agriculture is the insufficiently studied application of sensor networks under a complex set of specific interferences inherent to farm production. Optimizing packet transmission in WSNs over non-ideal radio channels has been widely explored, however, there is a lack of formalized methods for adaptive control of data packet size that comprehensively account for the influence of inter-node distance, signal-to-noise ratio (SNR), Rician K-factor, and temperature on the optimal fragmentation degree. The aim of this work is to develop and analyze an adaptive strategy for selecting data packet fragmentation degree to minimize endto-end (E2E) delay in WSNs under non-stationary fading channels. The methodology is based on analytical modeling of a Rician fading channel and the development of a time-cost model considering the ARQ protocol. The study proposes optimal fragmentation matrices that define a strategy minimizing delay for given SNR, K-factor, and temperature. The numerical simulations performed on a linear WSN confirm that transmitting packets in their entirety is efficient under favorable channel conditions, whereas deep fragmentation proves optimal as channel quality deteriorates, thereby optimizing the overall radio signal transmission process. The developed tool for the dynamic adaptation of transmission parameters in real-world WSNs enhances their reliability, reduces energy consumption, and ensures the timely delivery of data for automated control systems in the agricultural sector.

Author Biography

Vladimir V. Samoylenko, Stavropol State Agrarian University

Cand. Sci. (Eng.), Associate Professor, Department of Engineering and IT Solutions

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