An Adaptive Low-Power Listening Protocol for Wireless Sensor Networks in Noisy Environments

This paper investigates the energy consumption minimization problem for wireless sensor networks running low-power listening (LPL) protocols in noisy environments. We observe that the energy consumption by false wakeups (i.e., wakeup without receiving any packet) of a node in noisy environments can be a dominant factor in many cases while the false wakeup rate is spatially and temporarily dynamic. Based on this observation, without carefully considering the impact of false wakeups, the energy efficient performance of LPL nodes in noisy environments may significantly deviate from the optimal performance. To address this problem, we propose a theoretical framework incorporating LPL temporal parameters with the false wakeup rate and the data rate. We then formulate an energy consumption minimization problem of LPL in noisy environments and address the problem by a simplified and practical approach. Based on the theoretical framework, we design an efficient adaptive protocol for LPL (APL) in noisy environments. Through extensive experimental studies with Telosb nodes in real environments, we show that APL achieves 20%-40% energy efficient improvement compared to existing LPL protocols under various network conditions.