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Abstract
In-network data aggregation is a fundamental traffic pattern in many applications of wireless sensor networks (WSNs). Data aggregation scheduling aims to find a collisionfree transmission schedule scheme for data aggregation while minimizing the total network latency. This paper focuses on the data aggregation scheduling problem in dutycycled WSNs (dc-WSNs), in which low-duty-cycle techniques are employed for energyconsuming operations. Based on greedy strategy, we propose two latency-efficient data aggregation scheduling algorithms, namely GAS-PAS and GAS-SAS for dc-WSNs. We theoretically derive the latency upper bounds of the proposed algorithms, and the results demonstrate that both GAS-PAS and GAS-SAS achieve constant approximation to the optimal latency. We also conduct extensive simulations to show that the proposed scheduling algorithms can improve data aggregation latency in dc-WSNs under various network settings, comparing with state-of-the-art algorithms in the literature.
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