Energy-Optimal Control of Multiple Smart Sensors With Faulty External Signal

For multiple smart sensors (MSSs) operating with limited energy, the external signal (ES) often serves an indispensable role in enabling them to report their sensing data, reflecting the physical world with tolerable sensing errors. However, due to interior disturbances lurking in the MSSs or exterior noises originating from practical environments, the ES may become faulty for some smart sensors and subsequently affect the sensor connections. This not only deteriorates sensing errors but also wastes energy. Therefore, addressing the problem of assuring MSSs to report tolerable sensing errors with minimum energy consumption under the faulty ES (FES) emerges as an interesting and challenging issue. To address this problem, this paper first formulates MSSs as a temporal multiple input multiple output (MIMO) system, considering all the ESs and sensing errors as the input and output, respectively. It then reveals a necessary and sufficient condition for MSSs to determine whether or not to update the sensor connections, discloses a criterion guiding MSSs in performing such updates, and finally determines the optimal ES in terms of controlling MSSs to report tolerable sensing errors with the minimum energy consumption under the FES. An algorithm based on our discovered theoretical foundations is further proposed to implement such an optimal ES. The theoretical analysis and experiments against existing methods validate its performance.

Automated summary

This paper addresses the problem of ensuring multiple smart sensors report tolerable sensing errors with minimum energy consumption under faulty external signals (ES). It formulates the sensors as a temporal multiple input multiple output (MIMO) system and reveals the necessary conditions for updating sensor connections. An algorithm is proposed to implement the optimal ES, and theoretical analysis and experiments validate its performance.