LESS: Link Estimation with Sparse Sampling in Intertidal WSNs

Deploying wireless sensor networks (WSN) in the intertidal area is an effective approach for environmental monitoring. To sustain reliable data delivery in such a dynamic environment, a link quality estimation mechanism is crucial. However, our observations in two real WSN systems deployed in the intertidal areas reveal that link update in routing protocols often suffers from energy and bandwidth waste due to the frequent link quality measurement and updates. In this paper, we carefully investigate the network dynamics using real-world sensor network data and find it feasible to achieve accurate estimation of link quality using sparse sampling. We design and implement a compressive-sensing-based link quality estimation protocol, [Formula: see text] , which incorporates both spatial and temporal characteristics of the system to aid the link update in routing protocols. We evaluate [Formula: see text] in both real WSN systems and a large-scale simulation, and the results show that [Formula: see text] can reduce energy and bandwidth consumption by up to [Formula: see text] while still achieving more than [Formula: see text] link quality estimation accuracy.