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Emission Scheduling Strategies for Massive-IoT: Implementation and Performance Optimization
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DOI：10.1109/NOMS54207.2022.9789769.png)
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Abstract
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In today's monitoring solutions, each application involves custom deployment and requires significant configuration efforts to accommodate sensor changes. In contrast, in this paper, we consider a massive deployment of battery-powered sensors to propose a more versatile monitoring solution that is not tied to the physical deployment of devices. First, we define a framework for the definition of a monitoring strategy, for which we propose a generic monitoring accuracy metric, which, weighted to the lifetime of the monitoring network, allows the characterization of a multi-objective problem. We then introduce a specific two-parameter instantiation for the period update function, that ensures strictly periodic emissions from sensors even when new sensors join the system over time. We show through simulations how the two parameters- target emission period and number of jointly used sensors-can be chosen according to the objectives for the monitoring, by highlighting the Pareto front for accuracy and energy-efficiency.
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