Abstract
Radio signal strength (RSS) is an attractive property since it can be obtained without additional hardware. Based on various signal propagation models that describe the relationship between RSS and distance, RSS can be employed in network connectivity, localization, and link quality issues in wireless sensor networks (WSNs). However, the deterministic propagation models, in which RSS is only determined by distance, are far from reality. We carefully design a series of experiments using MICA2 nodes in real environments to investigate the parameters besides distance—frequency, variation of transceivers, antenna orientation, battery voltage, temporal-spatial properties of environment, and environmental dynamics. All the parameters contribute to RSS irregularity, which can highly affect the design of localization and topology control algorithms in wireless sensor networks. We derive the log-normal error model for RSS-based distance estimation from the underlying propagation models and find out that the popular noisy disk error model always underestimates distance error in localization. A quality-based localization algorithm is proposed to handle the large error in RSS-based distance estimation. In WSNs, topology control achieves energy-efficiency by turning off redundant nodes, while still satisfying the given network requirement. We first propose several connectivity-based topology control algorithms, which assume that links are either connected or disconnected. As our experiments show that, besides the connected and disconnected region, a large number of links reside in the transitional region with fluctuating link quality. We then propose a link-quality-based topology control algorithm, which employ opportunistic transmission to catch the best transmission opportunities on transitional links. Our simulations demonstrate that opportunistic transmission can significantly improve energy-efficiency in topology control with low communication overhead. To the best of our knowledge, we are the first to consider link quality and apply opportunistic communication in topology control for WSNs.
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