ПРОГНОЗИРОВАНИЕ ВРЕМЕНИ РАБОТЫ БЕСПРОВОДНЫХ СЕНСОРНЫХ СЕТЕЙ НА ОСНОВЕ ТЕХНОЛОГИИ LORA С ИСПОЛЬЗОВАНИЕМ ВЕРОЯТНОСТНОЙ МОДЕЛИ МАРКОВСКИХ ЦЕПЕЙ

Abstract

Real-time monitoring systems and sensors are not complete without wireless data transmission modules. Improving energy efficiency requires examining various system parameters that affect the power consumption of transmitting and receiving devices. The most important parameter of any autonomous wireless network is its uptime. In this work, we used LoRa wireless modules on the SX1278 chip manufactured by Semtech to determine their power consumption in various operating modes. The obtained data were used to build a consumption model of the device when connected to a receiver. Three operating modes are considered: transmit mode, receive mode and sleep mode. In an ideal communication channel, all transmitted data reaches the receiver with 100% probability. In a real situation, data reaches the receiver with a certain probability, depending on the communication channel, transmission power, distance to the addressee, and network parameters. In this work, the occurrence of an error is random. In this case, the occurrence of an error during reception entails a lack of confirmation of receipt or a request for re-sending data. Sending data again increases the power consumption of the device and, consequently, decreases the operating time of the wireless device. This paper shows the dependences of the operating time on various initial monitored parameters of the device, such as: confirmation timeout, packet length, time of one transmission cycle and the maximum number of retransmissions in one cycle. The developed model for predicting the consumption of the device can be used in the design of autonomous wireless sensor monitoring networks.