wireless sensor nodes;
Protocols;
low-power wide-area network (LPWAN);
Batteries;
Battery lifetime;
optimized transmission strategies;
Analytical models;
Wireless sensor networks;
statistical model checking (SMC);
Automata;
Model checking;
Sensors;
design space exploration;
期刊名称：
IEEE sensors journal
i s s n：
1530-437X
年卷期：
2023 年
23 卷
10 期
页 码：
10577-10587
页 码：
摘 要：
Wireless sensor nodes are usually powered by batteries that have limited energy capacity. In many applications, the nodes are installed in inaccessible locations where they are problematic to replace or recharge. Therefore, energy optimization is crucial for increasing the node’s lifetime. This study presents a method for the analysis and prediction of the energy consumption of Sigfox-based wireless sensor nodes. The method is illustrated in a use case where the nodes monitor the water level in drainage lines in cities to improve surface and wastewater management. We propose a formal model-based technique using the UPPAAL statistical model checker tool to model and analyze the node’s lifetime. Statistical model checking (SMC) provides a highly scalable technique for the performance analysis of complex cyber-physical systems. The model captures the energy-related behavior of the node, the Sigfox radio specification, and the sensor, each parameterized with values from the device’s datasheets. Furthermore, we calibrate the model using measurements obtained from real-world hardware. Finally, we evaluate a collection of strategies to optimize the battery lifetime of the node. We simulate the model with a 10000-mAh battery, and the results indicate that we can extend the node’s lifetime from 202 days to 2.71 years using our most optimized transmission strategy.
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