Data-driven Link Estimation in Low-power Wireless Networks : An Accuracy Perspective

Link estimation is a basic element of routing in low-power wireless networks, and several approaches using broadcast beacons and/or unicast MAC feedback have been proposed in the past years. No netheless, there has been no systematic study on the inherent draw backs of beacon-based link estimation and the subtleties of data-dr iven link estimation. Using a testbed of 98 XSM motes (an enhanced version o f MICA2 motes), we characterize the inherent errors in predicting unicast properties via broadcast beacons, and we show that data-driven lin k estimation and routing achieves higher event reliability (e.g., by up t o 18.75%) and energy efficiency (e.g., by up to a factor of 1.96) than beacon -based approaches. Through mathematical and experimental analysis , we examine the accuracies of different data-driven link estimation methods and their impacts on routing performance. We discover, counterintui tively, that two representative, seemingly similar methods of data-dri ven link estimation differ significantly in performance: in our testbed, for instance, data delivery reliability differs by 25.18%, and energy efficiency differs by a factor of 3.75. These findings provide new insight into the su btle design decisions in link estimation that significantly impact routing performance in low-power wireless networks. Keywords—Low-power wireless networks, sensor networks, link estimation and routing, data-driven, beacon-based

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