Experimental Analysis of Link Estimation Methods in Low Power Wireless Networks

Wireless sensor networks are envisioned to be an integral part of cyber-physical systems, yet wireless networks are inherently dynamic and come with various uncertainties. One such uncertainty is wireless communication itself which assumes complex spatial and temporal dynamics. For dependable and predictable performance, therefore, link estimation has become a basic element of wireless network routing. Several approaches using broadcast beacons and/or unicast MAC feedback have been proposed in the past years, but there is still no systematic characterization of the drawbacks and sources of errors in beacon-based link estimation in low-power wireless networks, which leads to ad hoc usage of beacons in routing. Using a testbed of 98 XSM motes (an enhanced version of MICA2 motes), we characterize the negative impact that link layer retransmission and traffic-induced interference have on the accuracy of beacon-based link estimation, and we show that data-driven link estimation and routing achieve higher event reliability (e.g., by up to 18.75%) and transmission efficiency (e.g., by up to a factor of 1.96) than beacon-based approaches. These findings provide solid evidence for the necessity of data-driven link estimation and demonstrate the importance of addressing the drawbacks of beacon-based link estimation when designing protocols for low-power wireless networks of cyber-physical systems.